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Journal articles on the topic 'Analog image'

Author: Grafiati

Published: 7 June 2025

Last updated: 17 July 2025

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1

Hasler, Jennifer, and Praveen Raj Ayyappan. "An Analog Architecture and Algorithm for Efficient Convolutional Neural Network Image Computation." Journal of Low Power Electronics and Applications 15, no. 3 (2025): 37. https://doi.org/10.3390/jlpea15030037.

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This article presents an energy-efficient IC architecture implementation of an analog image-processing ML system, where the primary issue is analog architecture development for existing energy-efficient analog computing devices. An architecture is developed for image classification, transforming a typical imager input into a classified result using a particular NN algorithm, a convolutional NN (ConvNN). These efforts show the need to continue to develop energy-efficient analog architectures alongside efficient analog circuits to fully exploit the opportunities of analog computing for system application.

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Kim, Chungyong, and Gyu-Sik Kim. "Analog CMOS Image Sensor-based Radon Counter." International Journal of Trend in Scientific Research and Development Volume-2, Issue-2 (2018): 54–59. http://dx.doi.org/10.31142/ijtsrd8330.

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Choi, Jaihyuk, Sungjae Lee, Youngdoo Son, and Soo Youn Kim. "Design of an Always-On Image Sensor Using an Analog Lightweight Convolutional Neural Network." Sensors 20, no. 11 (2020): 3101. http://dx.doi.org/10.3390/s20113101.

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This paper presents an always-on Complementary Metal Oxide Semiconductor (CMOS) image sensor (CIS) using an analog convolutional neural network for image classification in mobile applications. To reduce the power consumption as well as the overall processing time, we propose analog convolution circuits for computing convolution, max-pooling, and correlated double sampling operations without operational transconductance amplifiers. In addition, we used the voltage-mode MAX circuit for max pooling in the analog domain. After the analog convolution processing, the image data were reduced by 99.58% and were converted to digital with a 4-bit single-slope analog-to-digital converter. After the conversion, images were classified by the fully connected processor, which is traditionally performed in the digital domain. The measurement results show that we achieved an 89.33% image classification accuracy. The prototype CIS was fabricated in a 0.11 μm 1-poly 4-metal CIS process with a standard 4T-active pixel sensor. The image resolution was 160 × 120, and the total power consumption of the proposed CIS was 1.12 mW with a 3.3 V supply voltage and a maximum frame rate of 120.

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Sasaki, Mamoru, and Hirokuni Fujiyama. "An analog VLSI for analog-to-binary image conversion." Electronics and Communications in Japan (Part III: Fundamental Electronic Science) 84, no. 4 (2000): 11–20. http://dx.doi.org/10.1002/1520-6440(200104)84:4<11::aid-ecjc2>3.0.co;2-n.

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Balsa, Jose, Tomás Domínguez-Bolano, Óscar Fresnedo, José A. García-Naya, and Luis Castedo. "Image Transmission: Analog or Digital?" Proceedings 2, no. 18 (2018): 1163. http://dx.doi.org/10.3390/proceedings2181163.

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Hattori, S. "Image Manipulation: Digital Versus Analog." Endoscopy 24, S 2 (1992): 506–8. http://dx.doi.org/10.1055/s-2007-1010531.

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7

Andreadis, I., and Ph Tsalides. "Analog Computation of Image Chromaticity." Real-Time Imaging 3, no. 1 (1997): 1–6. http://dx.doi.org/10.1006/rtim.1996.0041.

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FRAME, MICHAEL, and NIAL NEGER. "FRACTAL VIDEOFEEDBACK AS ANALOG ITERATED FUNCTION SYSTEMS." Fractals 16, no. 03 (2008): 275–85. http://dx.doi.org/10.1142/s0218348x08003946.

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We demonstrate that videofeedback augmented with one or two mirrors can produce stationary fractal patterns obtained by an iterated function system (IFS) with two transformations (one with a reflection, one without), and with four transformations (two with reflections, one without, one with a 180° rotation). Camera placement yielding only a partial image in one or both mirrors can be achieved using IFS with memory. The IFS rules are obtained from the images of three non-collinear points in each of the principal pieces of the image.

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Shimonomura, Kazuhiro, Seiji Kameda, Kazuo Ishii, and Tetsuya Yagi. "A Novel Robot Vision Employing a Silicon Retina." Journal of Robotics and Mechatronics 13, no. 6 (2001): 614–20. http://dx.doi.org/10.20965/jrm.2001.p0614.

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A Robot vision system was designed using a silicon retina, which has been developed to mimick the parallel circuit structure of the vertebrate retina. The silicon retina used here is an analog CMOS very large-scale integrated circuit, which executes Laplacian-Gaussian like filtering on the image in real time. The processing is robust to change of illumination condition. Analog circuit modules were designed to detect the contour from the output image of the silicon retina and to binarize the output image. The images processed by the silicon retina as well as those by the analog circuit modules are received by the DOS/V-compatible mother-board with NTSC signal, which enables higher level processings using digital image processing techniques. This novel robot vision system can achieve real time and robust processings in natural illumination condition with a compact hardware and a low power consumption.

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Raghavendra, V., N. Vinay kumar, and Manish Kumar. "Latest advancement in image processing techniques." International Journal of Engineering & Technology 7, no. 2.12 (2018): 390. http://dx.doi.org/10.14419/ijet.v7i2.12.11357.

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Image processing is method of performing some operations on an image, for enhancing the image or for getting some information from that image, or for some other applications is nothing but Image Processing [1]. Image processing is one sort of signal processing, where input is an image and output may be an image, characteristics of that image or some features that image [1]. Image will be taken as a two dimensional signal and signal processing techniques will be applied to that two dimensional image. Image processing is one of the growing technologies [1]. In many real time applications image processing is widely used. In the field of bio technology, computer science, in medical field, envi-ronmental areas etc., image processing is being used for mankind benefits. The following steps are the basics of image processing:Image is taken as an inputImage will be processed (manipulation, analyzing the image, or as per requirement)Altered image will be the outputImage processing is of two typesAnalog Image Processing:As the name implies, analog image processing is applied on analog signals. Television image is best example of analog signal processing [1].(DIP) Digital Image Processing:DIP techniques are used on images, which are in the format of digital for processing them, and get the required output as per the application. Operations were applied on the digital images for processing [1].In this paper, we will discuss about the technologies or tools for image processing especially by using Open CV. With the help of Open CV image processing will be very easy and efficient. When Open CV is collaborated or integrated with python the results are mind blowing. We will discuss about the process of using python and Open CV.

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11

Frediani, Maria E. B., Thomas M. Hopson, Joshua P. Hacker, Emmanouil N. Anagnostou, Luca Delle Monache, and Francois Vandenberghe. "Object-Based Analog Forecasts for Surface Wind Speed." Monthly Weather Review 145, no. 12 (2017): 5083–102. http://dx.doi.org/10.1175/mwr-d-17-0012.1.

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Analogs are used as a forecast postprocessing technique, in which a statistical forecast is derived from past prognostic states. This study proposes a method to identify analogs through spatial objects, which are then used to create forecast ensembles. The object-analog technique preserves the field’s spatial relationships, reduces spatial dimensionality, and consequently facilitates the use of artificial intelligence algorithms to improve analog selection. Forecast objects are created with a three-step object selection, combining standard image processing algorithms. The resulting objects are used to find similar forecasts in a training set with a similarity measure based on object area intersection and magnitude. Storm-induced power outages in the Northeast United States motivated the method’s validation for 10-m AGL wind speed forecasts. The training set comprises reforecasts and reanalyses of events that caused damages to the utility infrastructure. The corresponding reanalyses of the best reforecast analogs are used to produce the object-analog ensemble forecasts. The forecasts are compared with other analog forecast methods. Analogs representing lower and upper predictability limits provide references to distinguish the method’s ability (to find good analogs) from the training set’s ability (to provide good analogs) to generate skillful ensemble forecasts. The object-analog forecasts are competitively skillful compared to simpler analog techniques with an advantage of lower spatial dimensionality, while generating reliable ensemble forecasts, with reduced systematic and random errors, maintaining correlation, and improving Brier scores.

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Xiaohua, Wang, Liu Dongsheng, Xuan Xiao, Duan Jianghui, and Yuan Huishu. "Influence of tube voltage on digitized image qualityof patients exposed to occupational dust: phantoms and clinical studies." Chinese Medical Journal 127, no. 16 (2014): 2940–44. http://dx.doi.org/10.3760/cma.j.issn.0366-6999.20140449.

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Background High-voltage analog X-ray examination is a main tool for pneumoconiosis, which is challenged by digital radiography (DR). The tube voltage of DR chest films required for diagnosis and staging of pneumoconiosis is concerned technically. We investigated the influence of the tube voltage on chest X-ray DR image quality of patients exposed to occupational dust. Methods DR images of the CDRAD2.0model, an anatomical chest phantom, and 136 exposed workers were analyzed at different tube voltages by threereaders. Image quality factors (IQF) were calculated and compared using the CDRAD2.0 model. DR images of ten anatomic positions were scored against those of the high-kilovolt chest films in anatomical phantom and clinical cases, and differences in scores were analyzed. Results In the CDRAD2.0 model, all three readers had a minimal IQF at 120 kV (mean: 22.25 kV). The differences in the mean IQF of DR images at different tube voltages was significant (F=13.78, P<0.001). The IQF of DR imaging at 120 kV was similar to high kilovolt analog imaging (t=-0.58, P>0.05). In the anatomic phantom and clinical cases, the DR images at 120 kV were closest in anatomical detail to the high kV analog images, and the means were similar (P>0.05). Conclusions Among different tube voltages, DR image quality is closest to the high kilovolt analog images at 120 kV in patients exposed to occupational dust.

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Zambrano, Benjamin, Sebastiano Strangio, Tommaso Rizzo, Esteban Garzón, Marco Lanuzza, and Giuseppe Iannaccone. "All-Analog Silicon Integration of Image Sensor and Neural Computing Engine for Image Classification." IEEE Access 10 (September 1, 2022): 94417–30. https://doi.org/10.1109/ACCESS.2022.3203394.

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We have designed a fully-integrated analog CMOS cognitive image sensor based on a two-layer artificial neural network and targeted to low-resolution image classification. We have used a single poly 180 nm CMOS process technology, which includes process modules for realizing the building blocks of the CMOS image sensor. Our design includes all the analog sub-circuits required to perform the cognitive sensing task, from image sensing to output classification decision. The weights of the network are stored in single-poly floating-gate memory cells, using a single transistor per analog weight. This enables the classifier to be intrinsically reconfigurable, and to be trained for various classification problems, based on low-resolution images. As a case study, the classifier capability is tested using a low-resolution version of the MNIST dataset of handwritten digits. The circuit exhibits a classification accuracy of 87.8%, that is comparable to an equivalent software implementation operating in the digital domain with floating point data precision, with an average energy consumption of 6 nJ per inference, a latency of 22.5 μs and a throughput of up to 133.3 thousand inferences per second.

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14

Balsa, Jose. "Comparison of Image Compressions: Analog Transformations." Proceedings 54, no. 1 (2020): 37. http://dx.doi.org/10.3390/proceedings2020054037.

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A comparison between the four most used transforms, the discrete Fourier transform (DFT), discrete cosine transform (DCT), the Walsh–Hadamard transform (WHT) and the Haar-wavelet transform (DWT), for the transmission of analog images, varying their compression and comparing their quality, is presented. Additionally, performance tests are done for different levels of white Gaussian additive noise.

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Chong, C. P., C. A. T. Salama, and K. C. Smith. "Image-motion detection using analog VLSI." IEEE Journal of Solid-State Circuits 27, no. 1 (1992): 93–96. http://dx.doi.org/10.1109/4.109560.

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Yang, Bin, Yan Chang Wang, Pei Hong Li, and Ji Lin Liu. "HDR CCD Image Sensor System through Double-A/D Convertors." Applied Mechanics and Materials 66-68 (July 2011): 2241–47. http://dx.doi.org/10.4028/www.scientific.net/amm.66-68.2241.

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In this paper we present a CCD image sensor system with high dynamic range. This feature is achieved through double analog-to-digital convertors’(ADC) architecture and field programmable gate arrays(FPGA). By doing so, the system outputs high dynamic range images in real time. The proposed scheme is a low-cost solution in the sense that it can be built on top of any traditional sensor system with minor modifications on the system-level analog-to-digital module. Through the post-layout sensor system we show the experimental images to demonstrate the effectiveness.

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Rajneesh, Narula*1 &. Manpreet Kaur2. "A RECENT APPROACH TO IMAGE EDGE DETECTION BY THE IMPLEMENTATION OF RULE BASED FUZZY LOGIC." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 6, no. 1 (2019): 194–200. https://doi.org/10.5281/zenodo.2551751.

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Image processing is any form of information processing for which both the input and output are images, such as photographs or frames of video. Most image processing techniques involve treating the image as a two-dimensional matrix. A few decades ago, image processing was done largely in the analog domain, chiefly by optical devices. There is also much massively parallel architecture that has been developed for the purpose.

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De Silva, Kalupahanage Dilusha Malintha, and Hyo Jong Lee. "Distorted Aerial Images Semantic Segmentation Method for Software-Based Analog Image Receivers Using Deep Combined Learning." Applied Sciences 13, no. 11 (2023): 6816. http://dx.doi.org/10.3390/app13116816.

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Aerial images are important for monitoring land cover and land resource management. An aerial imaging source which keeps its position at a higher altitude, and which has a considerable duration of airtime, employs wireless communications for sending images to relevant receivers. An aerial image must be transmitted from the image source to a ground station where it can be stored and analyzed. Due to transmission errors, aerial images which are received from an image transmitter contain distortions which can affect the quality of the images, causing noise, color shifts, and other issues that can impact the accuracy of semantic segmentation and the usefulness of the information contained in the images. Current semantic segmentation methods discard distorted images, which makes the available dataset small or treats them as normal images, which causes poor segmentation results. This paper proposes a deep-learning-based semantic segmentation method for distorted aerial images. For different receivers, distortions occur differently, and by considering the receiver specificness of the distortions, the proposed method was able to grasp the acceptability for a distorted image using semantic segmentation models trained with large aerial image datasets to build a combined model that can effectively segment a distorted aerial image which was received by an analog image receiver. Two combined deep learning models, an approximating model, and a segmentation model were trained combinedly to maximize the segmentation score for distorted images. The results showed that the combined learning method achieves higher intersection-over-union (IoU) scores than the results obtained by using only a segmentation model.

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Ransick, Mark H., and Chadwick D. Barklay. "Interfacing a Personal Computer to an Analog Scanning Electron Microscope for Storing Images on Optical Disks." Proceedings, annual meeting, Electron Microscopy Society of America 48, no. 2 (1990): 84–85. http://dx.doi.org/10.1017/s0424820100134016.

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Most manufacturers of scanning electron microscopes (SEM) now offer models that display an image digitally. This holds many advantages, including the ability to store the image on a disk and perform image analysis on the sample. Most SEMs in service, however, produce only an analog video output; they do not have the ability to digitize the image. Film is the only method of storing images.Consequentially, film is a significant portion of every microscopy laboratory’s budget. Completely eliminating the use of film from use is not practical. There will always be the need to examine a hard copy of the image; many programs require duplicate copies of each image generated; and it is sound practice to keep a copy of each image on file. By archiving digital images to an inexpensive media, the amount of film used or the time devoted to processing negatives can be greatly reduced.By using personal computers (PCs)s, with a digitizing board and analog to digital (A/D) board, it is possible to construct a relatively low cost digitizing system for any SEM.

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Wu, Chenxu, Yibai Xue, Han Bao, et al. "Forward stagewise regression with multilevel memristor for sparse coding." Journal of Semiconductors 44, no. 10 (2023): 104101. http://dx.doi.org/10.1088/1674-4926/44/10/104101.

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Abstract Sparse coding is a prevalent method for image inpainting and feature extraction, which can repair corrupted images or improve data processing efficiency, and has numerous applications in computer vision and signal processing. Recently, several memristor-based in-memory computing systems have been proposed to enhance the efficiency of sparse coding remarkably. However, the variations and low precision of the devices will deteriorate the dictionary, causing inevitable degradation in the accuracy and reliability of the application. In this work, a digital-analog hybrid memristive sparse coding system is proposed utilizing a multilevel Pt/Al2O3/AlOx/W memristor, which employs the forward stagewise regression algorithm: The approximate cosine distance calculation is conducted in the analog part to speed up the computation, followed by high-precision coefficient updates performed in the digital portion. We determine that four states of the aforementioned memristor are sufficient for the processing of natural images. Furthermore, through dynamic adjustment of the mapping ratio, the precision requirement for the digit-to-analog converters can be reduced to 4 bits. Compared to the previous system, our system achieves higher image reconstruction quality of the 38 dB peak-signal-to-noise ratio. Moreover, in the context of image inpainting, images containing 50% missing pixels can be restored with a reconstruction error of 0.0424 root-mean-squared error.

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Li, Xingxing, Panpan Yin, Chao Duan, and Yan Zhi. "Analog Gauge Reader based on Image Recognition." Journal of Physics: Conference Series 1650 (October 2020): 032061. http://dx.doi.org/10.1088/1742-6596/1650/3/032061.

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Lohmann, Joachim, and Johannes Willsau. "Analog Image Processing in Modern Color Photography." Journal of Imaging Science and Technology 43, no. 6 (1999): 550–59. http://dx.doi.org/10.2352/j.imagingsci.technol.1999.43.6.art00011.

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23

Chungyong, Kim, and Kim Gyu-Sik. "Analog CMOS Image Sensor based Radon Counter." International Journal of Trend in Scientific Research and Development 2, no. 2 (2018): 54–59. https://doi.org/10.31142/ijtsrd8330.

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Radon is an invisible, odorless, and chemically inactive radioactive gas produced by the decay of uranium ore. Various types of equipment and components have been proposed for use in effective radon detection. In this paper, we describe a radon detector that uses an analog CMOS image sensor module. Based on our studies, we believe that this system would be helpful in protecting many people from the dangers associated with radon exposure. Chungyong Kim | Gyu-Sik Kim "Analog CMOS Image Sensor-based Radon Counter" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-2 , February 2018, URL: https://www.ijtsrd.com/papers/ijtsrd8330.pdf

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Yegana Aliyeva, Yegana Aliyeva, and Agil Mammadli Agil Mammadli. "DEVELOPMENT OF IMAGE PROCESSING ALGORITHM UTILIZING NEURAL NETWORKS AND FUZZY LOGIC." ETM - Equipment, Technologies, Materials 16, no. 04 (2023): 59–66. http://dx.doi.org/10.36962/etm16042023-59.

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Despite their limitations, robots should have the ability to gather information from their surroundings such as location, color, light, and images. This data must then be analyzed automatically, and based on that analysis, the robot should be able to determine an appropriate reaction to its environment. Once a decision has been made, the robot must be able to execute it through the use of actuators and motion systems. Robots are comprised of sensors that collect real-time environmental data, an electronic brain that processes and decides, and movement controls that carry out those decisions. Images must be displayed as an analog signal during the image processing process. Video data, originally in the form of analog voltage, must be represented in the form of binary codes. This article deals with the development of image processing algorithm for industrial robots based on neural network and fuzzy logic. Keywords: image processing, fuzzy logic, pixel, robot, sensor.

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Noskov, Mikhail, Valeriy Tutatchikov, Mikhail Lapchik, Marina Ragulina, and Tatiana Yamskikh. "Application of parallel version two-dimensional fast Fourier transform algorithm, analog of the Cooley-Tukey algorithm, for digital image processing of satellite data." E3S Web of Conferences 75 (2019): 01012. http://dx.doi.org/10.1051/e3sconf/20197501012.

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In modern systems of remote sensing two-dimensional fast Fourier transform (FFT) has been widely used for digital processing of satellite images and subsequent image filtering. This article provides a parallel version two-dimensional fast Fourier transform algorithm, analog of the Cooley-Tukey algorithm and its implementation for processing the satellite image of Krasnoyarsk and its suburban areas.

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Kim, Han Seul, Da Sol Kim, and Jung Il Song. "A Study on Image Interpretations of Computed Radiography for Iron Samples Using Image Evaluation Techniques." Journal of Conservation Science 38, no. 5 (2022): 360–74. http://dx.doi.org/10.12654/jcs.2022.38.5.01.

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In the non-destructive radiographic testing methods used for specimens with cultural heritage, analog film radiography is being replaced with digital radiography by the introduction of an imaging plate computed radiography system. Adoption of the computed radiography system has helped standardize digital image quality.</br>This study analyzed the X-ray transmission characteristics and evaluated image quality according to image developing time for iron, the most important metal in cultural heritage. Computed radiography images were acquired. The transmittance of the images was determined based on Gray Scale and Duplex-wire Image Quality Indicator data. In addition, the change in images with the image developing time was compared and analyzed using the Structural Similarity Index Measure, mean square error, and peak signal-to-noise ratio.

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Kawahito, Shoji, and Kiyoharu Aizawa. "CMOS Image Sensor Dreams of Intelligent Sensors. Image Sensors with Analog Image Processing Function." Journal of the Institute of Image Information and Television Engineers 53, no. 2 (1999): 166–71. http://dx.doi.org/10.3169/itej.53.166.

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Li, Jiacheng, Honglei Wang, Xishuo Zhu, Sijian Liu, and Junsheng Zhang. "A Vision-Based Analog Meter Reading Method for Inspection Robots." Scalable Computing: Practice and Experience 25, no. 5 (2024): 4205–17. http://dx.doi.org/10.12694/scpe.v25i5.2986.

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Computer vision technology has been widely applied in reading recognition of analog meters. However, it is still a challenge to quickly and accurately read various types of analog meters under different environmental conditions. We propose a fast-reading method for analog meters based on keypoint detection, which is applied to inspection robots. First, we use the YOLOv5s network to locate the analog meter. Second, the HRNet network is used to detect the keypoints of the pointer and scale on the dial. Third, an objective image quality assessment method that includes multiple indicators is established to select the optimal image for reading recognition. Finally, we calculate the reading of the analog meter based on the deflection angle of the pointer. The experiment shows that our method can accurately read the readings of analog meters, with an average reading error of 3.81%. It can be effectively applied to inspection robots to read analog meter readings.

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Buhmann, Joachim M., Tilman Lange, and Ulrich Ramacher. "Image Segmentation by Networks of Spiking Neurons." Neural Computation 17, no. 5 (2005): 1010–31. http://dx.doi.org/10.1162/0899766053491913.

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A network of leaky integrate-and-fire (IAF) neurons is proposed to segment gray-scale images. The network architecture with local competition between neurons that encode segment assignments of image blocks is motivated by a histogram clustering approach to image segmentation. Lateral excitatory connections between neighboring image sites yield a local smoothing of segments. The mean firing rate of class membership neurons encodes the image segmentation. A weight modification scheme is proposed that estimates segment-specific prototypical histograms. The robustness properties of the network implementation make it amenable to an analog VLSI realization. Results on synthetic and real-world images demonstrate the effectiveness of the architecture.

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Jin, Minhyun, Hyeonseob Noh, Minkyu Song, and Soo Youn Kim. "Design of an Edge-Detection CMOS Image Sensor with Built-in Mask Circuits." Sensors 20, no. 13 (2020): 3649. http://dx.doi.org/10.3390/s20133649.

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In this paper, we propose a complementary metal-oxide-semiconductor (CMOS) image sensor (CIS) that has built-in mask circuits to selectively capture either edge-detection images or normal 8-bit images for low-power computer vision applications. To detect the edges of images in the CIS, neighboring column data are compared in in-column memories after column-parallel analog-to-digital conversion with the proposed mask. The proposed built-in mask circuits are implemented in the CIS without a complex image signal processer to obtain edge images with high speed and low power consumption. According to the measurement results, edge images were successfully obtained with a maximum frame rate of 60 fps. A prototype sensor with 1920 × 1440 resolution was fabricated with a 90-nm 1-poly 5-metal CIS process. The area of the 4-shared 4T-active pixel sensor was 1.4 × 1.4 µm2, and the chip size was 5.15 × 5.15 mm2. The total power consumption was 9.4 mW at 60 fps with supply voltages of 3.3 V (analog), 2.8 V (pixel), and 1.2 V (digital).

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Saeidiyan, Zeinab, Mohammad Hosein Fatehi, Mehdi Taghizadeh, and Mohammad Mehdi Ghanbarian. "Enhancing the Accuracy and Speed of Sampling in Image Sensors by Designing Analog to Digital Converter with Power Decrease Approach." Journal of Sensors 2022 (January 24, 2022): 1–16. http://dx.doi.org/10.1155/2022/5075823.

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Analog to digital converters (ADCs) enable the processing of real-world analog signals in the digital realm. These converters are widely used in sensor systems, medical components, multimedia systems, image sensors, and wireless sensor nodes. Today, in portable devices that are powered by batteries, low power consumption and small area are a major and important need. Therefore, methods that can reduce power consumption and area have a variety of applications and are of great importance. Power consumption is one of the most important features of an integrated analog to digital converter. In this paper, a new design of low-power and fast analog to digital converter is presented. This design is used for specific applications for image processing. The suggested approach for rereading the image for limited number of pixels was designed and simulated, showing a considerable power decrease compared to the suggested state that depends on the pixel values.

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Oliveira, Fernanda D. V. R., Hugo L. Haas, Jose Gabriel R. C. Gomes, and Antonio Petraglia. "CMOS Imager With Focal-Plane Analog Image Compression Combining DPCM and VQ." IEEE Transactions on Circuits and Systems I: Regular Papers 60, no. 5 (2013): 1331–44. http://dx.doi.org/10.1109/tcsi.2012.2226505.

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Breitsohl, Louis Levi. "Bearing Witness in Analog and Digital Witness Films: Ethical Aesthetics in Shoah [1985] and Waltz with Bashir [2008]." Genealogy 6, no. 1 (2022): 14. http://dx.doi.org/10.3390/genealogy6010014.

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In the ongoing and passionate debates over the digitalization of visual media, many questions about the ontology or materiality of the new digital image have been raised. Analog representation is often thought of in terms of indexicality and sometimes a naive belief in the truthfulness of the photographic image, whereas the digital image is, in a way, no longer an image anymore, but a set of data in flux, superficially coded and easy to manipulate. The following article examines how this shift to digitalization affects the ethical genre per se: the witness film. In a film analytical close reading of Claude Lanzmann’s Shoah and Ari Folman’s Waltz with Bashir, resonances become visible to psychoanalysis, Deleuzian film philosophy and the debates over the materiality of the analog and digital image. Lanzmann draws on a specific kind of indirect indexicality, which is highly interested in the psychic and embodied realities of surviving, witnessing and the passing of time, whereas Folman develops a politics of the powers of the false: truthfulness, accessibility and memorability are abolished in favor of false images, screen-memories and traumatic mis/representation, which are staged noticeably digital and altered, revolving around the impossibility to grasp the ungraspable.

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34

Lee, Suhyeon, Yu Chan Yun, Seung Min Heu, et al. "The Design of a Computer Vision Sensor Based on a Low-Power Edge Detection Circuit." Sensors 25, no. 10 (2025): 3219. https://doi.org/10.3390/s25103219.

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We propose a complementary metal-oxide-semiconductor (CMOS) image sensor (CIS) that performs edge mask computation and detection during the analog-to-digital (A/D) conversion process to output 1-bit edge images. By utilizing the characteristics of the edge that can obtain a 1-bit image, the edge mask and thresholding operations are performed simultaneously during the A/D conversion process, thereby reducing memory capacity along with a high number of frames per second (FPS). Additionally, by implementing a 1-bit analog-to-digital converter (ADC) instead of a high-resolution ADC and counter through the 1-bit edge data obtained from the edge mask operation, both static and dynamic power consumption are reduced. The proposed CIS, fabricated with a one-poly six-metal CIS process with a 4T-active pixel sensor, has a core area of 2.546 mm × 1.923 mm in a chip area of 2.558 mm × 4.3 mm. The total power consumption is 1.52 mW at 23 FPS, with power supplies of 2.8 V and 1.5 V for the analog domain and 1.5 V for the digital domain.

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35

R, Manikandan, Muruganantham Ponnusamy, and Jayasri Subramaniam. "MATHEMATICAL MORPHOLOGY BASED DIGITAL IMAGE ENHANCEMENT PROCESSING WITH CROSS SEPARATE BOUNDARY OBJECTS." ICTACT Journal on Image and Video Processing 12, no. 4 (2022): 2699–703. https://doi.org/10.21917/ijivp.2022.0383.

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In computer science, digital image processing is the use of computer algorithms to perform image processing on digital images. The Image processing as a subgroup or background of digital signal processing has many advantages over analog image processing. The Digital image processing allows the use of a wide range of algorithms for input data and avoids problems such as noise accumulation and signal distortion during the processing process. Because images are defined in two dimensions (perhaps more than two dimensions), image processing can be formatted into multi-dimensional systems. In this paper an effective Mathematical morphology model was proposed to enhance the quality of images. In this mode, the image is pre-processed and then the gradient is changed using a mathematical image system. Then, the edges are detected by the margin detection method based on the statistical data. This method removes the shadow contours caused by the lights, directly separates the boundaries of the objects and has an impact on the background noise suppression.

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36

Kodera, Yoshie. "Image Evaluation in Digital Age: What is the Different from Analog Image." Japanese Journal of Radiological Technology 68, no. 4 (2012): 509–18. http://dx.doi.org/10.6009/jjrt.2012_jsrt_68.4.509.

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37

Kwok Fai Hui and B. E. Shi. "Distortion in analog VLSI networks for image filtering." IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 46, no. 10 (1999): 1161–71. http://dx.doi.org/10.1109/81.795829.

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38

Bartolucci, G. "Image parameter modeling analog traveling-wave phase shifters." IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 49, no. 10 (2002): 1505–9. http://dx.doi.org/10.1109/tcsi.2002.803364.

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39

Lumsdaine, A., J. L. Wyatt, and I. M. Elfadel. "Nonlinear analog networks for image smoothing and segmentation." Journal of VLSI signal processing systems for signal, image and video technology 3, no. 1-2 (1991): 53–68. http://dx.doi.org/10.1007/bf00927834.

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40

Graf, H. P., C. R. Nohl, and J. Ben. "Image recognition with an analog neural net chip." Machine Vision and Applications 8, no. 2 (1995): 131–40. http://dx.doi.org/10.1007/bf01213478.

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41

Knoll, Michelle K., and A. Carver-Kubik. "In-Field Digital Photography and the Curation of Associated Records: Not All Prints Are Created Equal." Advances in Archaeological Practice 7, no. 3 (2019): 302–10. http://dx.doi.org/10.1017/aap.2019.17.

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AbstractWith the advent of commercially available digital cameras in the late 1990s resulting in the near-exclusion of analog photographic prints today, most archaeological repositories around the world have a mix of analog and digital photographic prints. That ratio is increasingly moving toward digital print processes, of which there are several types. To minimize the loss of image quality, collection managers must become familiar with the unique curation challenges of photographic prints from digitally created images. Likewise, creators of digital content must be aware that choices made when selecting a print process for reposit will have a direct effect on image and print permanence. Site photographs are critical evidence of archaeological activity, and so the preservation of digital prints is in the interest, and is the responsibility, of collection managers and archaeologists alike.

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42

Chen, Ying Jun, Zhong Hua Sun, and Huang Ping. "Study on Image Sensor Controlling Circuit for Wireless Endoscopic MEMS." Applied Mechanics and Materials 220-223 (November 2012): 1003–7. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.1003.

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In this paper the design and experiments of image sensor controlling circuit using in wireless endoscopic MEMS was studied. Through comparing the excellency and deficiency of various types of image sensors, and considering the working environment and requirements in the human body, it is pointed out that the CMOS image sensor with high integration density, low power consumption, small dimension and analog image signal output is suitable for the wireless endoscopic MEMS. By theoretically analyzing, the controlling circuits of two typical image sensors were designed successfully. The images captured in the animal experiments prove the validity of the designed circuits for the wireless endoscopic MEMS.

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43

Xu, Dingyu, Hua Yang, Wenhao Xu, Wenshuai Zhang, Kuiming Zeng, and Hailu Luo. "Inverse design of Pancharatnam–Berry phase metasurfaces for all-optical image edge detection." Applied Physics Letters 120, no. 24 (2022): 241101. http://dx.doi.org/10.1063/5.0090606.

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In recent decades, optical analog computing has attracted considerable interest in image processing and optical engineering. However, the optical analog computing system composed of traditional optical devices is bulky and difficult to integrate in practical applications. Here, we propose a method for inversely designing Pancharatnam–Berry phase metasurfaces based on specified optical computing. Derived from the evolution of the Pancharatnam–Berry phase on the Poincaré sphere, the special relationship between local optical axis structure and phase can be obtained. On this basis, we inversely design several metasurfaces and applied them into optical analog computing as well as all-optical image edge detection.

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44

Henzen, Alex, Todd Rockoff, Rob Clarke, and Rob Hannebauer. "65‐1: Invited Paper: The Advantages of “Clocked‐Analog” Video Transport in Source Driver ICs." SID Symposium Digest of Technical Papers 55, S1 (2024): 558–59. http://dx.doi.org/10.1002/sdtp.17138.

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To emphasize the advantages of this method, HYPHY has developed an image and video quality measurement method that demonstrates the image quality of Modulated Analog to be at least on par with traditional display driving. Consumer demand for higher resolution, higher frame rate, and deeper color displays is driving the data rates of the connected video systems to the limits of affordability. At current high‐end displays, like 4K gaming at 360 Hz frame rate or 8K TV's at >120 Hz frame rate, conventional data transports require parallel data‐ pairs plus equalization circuits to deliver the required video data. These accommodations increase cost, power and complexity.HYPHY's revolutionary ‘clocked‐analog’ video transport is the solution to this impasse, demonstrably delivering 10X more video payload per “wire‐hertz” than traditional methods, delivering equal or better image quality.To emphasize the advantages of this method, HYPHY has developed an image and video quality measurement method that demonstrates the image quality of Modulated Analog to be at least on par with traditional display driving.

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Poli, D., C. Casarotto, M. Strudl, E. Bollmann, K. Moe, and K. Legat. "USE OF HISTORICAL AERIAL IMAGES FOR 3D MODELLING OF GLACIERS IN THE PROVINCE OF TRENTO." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2020 (August 14, 2020): 1151–58. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2020-1151-2020.

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Abstract. Historical aerial images represent a source of information of great value for glacier monitoring, as they cover the area of interest at a well-defined epoch and allow for visual interpretation and metric analysis. Typically, the aerial images are used to produce orthophotos and manually digitize the perimeters of the glaciers for analysis of the surface extent of the glaciers, while the extraction of height information is more challenging due to data quality and characteristics. This article discusses the potential of historical aerial images for glacier modelling. More specifically, it analyses the impact of their coverage, radiometric- and geometric accuracy, state of preservation and completeness on the photogrammetric workflow. The data set used consists of scans of 300 (analog) aerial images acquired between August and October 1954 by the U.S. Air Force with a Fairchild KF7660 camera over the entire Province of Trento. For the modelling of the glaciers, different techniques such as manual stereoscopic measurement and dense image matching were tested on sample glaciers and the results were analysed in detail. Due to local radiometric saturation in a large part of the glacial surfaces and other disturbances affecting the historical images (e.g. scratches, scanning errors, dark shadows), dense image matching did not produce any valuable results, and stereo plotting could be used only on images (or image parts) with acceptable quality. The derived Digital Terrain Models (DTMs) were compared with a reference DTM obtained with dense image matching from digital aerial images acquired in September 2015 with an UltraCam Eagle sensor, and, for some glaciers, to a DTM obtained with dense image matching from scanned aerial images acquired in September 1983 with a RC30 analog camera. The differences between 1954 and 2015 DTMs showed values up to 70–80 m in height and a behaviour that is confirmed by the models employed by the glaciology experts in Trento.

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46

Ivon, A. I., V. F. Istushkin, and V. O. Belugina. "SOFTWARE FOR SCANNING THE BRIGHTNESS OF THE RASTER IMAGES PIXELS." System technologies 1, no. 144 (2023): 13–19. http://dx.doi.org/10.34185/1562-9945-1-144-2023-02.

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A web-application for scan by program way of the analog oscillograms raster images when measuring the parameters of pulsed signals is described. As a criterion for selecting scan-ning points the maximum brightness of pixels on the signal lines of the oscillogram raster image is using.

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47

Chen, Ya. "Digital Image Acquisition and Presentation for High Resolution SEM." Microscopy and Microanalysis 4, S2 (1998): 68–69. http://dx.doi.org/10.1017/s1431927600020468.

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Images obtained from an analog SEM are traditionally viewed and recorded from a cathode-ray tube (CRT). Many laboratories use instant film (e.g. Polaroid #52, #55 instant film) to justify image quality and obtain permanent image quickly. Digital imaging provides an alternative approach for image acquisition and recording. One major advantage of digital SEM is image averaging that allows one to improve the signal-to-noise ratio (SNR) from a noisy quick-scan image to reduce charging. SEM signal yield is proportional to incident beam intensity, image acquisition time or duration of beam interaction with specimen (dwell time). The higher beam intensity, or longer the dwell time, the more signal generated. However, for high-resolution SEM imaging, the beam dose and dwell time are limited by drafting, radiation damage, and contamination. Therefore high-resolution biological SEM images invariably have poor SNR.

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48

Henzen, Alex, Todd Rockoff, and Will Caulkins. "47‐2: Invited Paper: Modulated Analog Driving and Evaluation of Image Quality." SID Symposium Digest of Technical Papers 55, no. 1 (2024): 627–29. http://dx.doi.org/10.1002/sdtp.17602.

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Consumer demand for higher resolution, higher frame rate, and deeper color displays is driving the data rates of the connected video systems to the limits of affordability. At current high‐end displays, like 4K gaming at 360 Hz frame rate or 8K TV's at >120 Hz frame rate, conventional data transports require parallel data‐pairs plus equalization circuits to deliver the required video data. These accommodations increase cost, power and complexity.HYPHY's revolutionary ‘modulated analog' (also referred to as “sampled Analog”) video transport is the solution to this impasse, demonstrably delivering 10X more video payload per “wire‐hertz” than traditional methods, delivering equal or better image quality.To emphasize the advantages of this method, HYPHY has developed an image and video quality measurement method that demonstrates the image quality of Modulated Analog to be at least on par with traditional display driving.

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49

Peters, Klaus-Ruediger. "The Digital Precision Imaging Laboratory Part I: The New Tools of Differential Contrast Imaging." Microscopy Today 4, no. 2 (1996): 16–17. http://dx.doi.org/10.1017/s1551929500067523.

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In recent years, many developments in imaging instrumentation and support technologies have put in question the conventional way of working with images. Conversion from analog to digital imaging is pursued at all levels of microscopy driven by the benefits of new forthcoming digital precision imaging technologies for visualization and quantification of the image information. These developments will revolutionize microscopy by extending the information retrieval from the level of the full-frame image to the level of individual pixels.

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Mansfield, John. "Basic Introduction to Image Processing Using NIH-lmage as a Model." Microscopy Today 2, no. 9 (1994): 15. http://dx.doi.org/10.1017/s1551929500067675.

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Advances in camera technology and digital instrument control have meant that in modern microscopy, the image that was, in the past, typically recorded on a piece of film is now recorded directly into a computer. The transfer of the analog image seen in the microscope to the digitized picture in the computer does not mean, however, that the problems associated with recording images, analyzing them, and preparing them for publication, have all miraculously been solved. The steps involved in the recording of an image to film remain largely intact in the digital world. The image is recorded, prepared for measurement in some way, analyzed, and then prepared for presentation.

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