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Journal articles on the topic 'Assessment of image'

Author: Grafiati

Published: 14 March 2023

Last updated: 31 July 2025

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1

Golub, Y. I. "Image quality assessment." «System analysis and applied information science», no. 4 (January 5, 2022): 4–15. http://dx.doi.org/10.21122/2309-4923-2021-4-4-15.

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Quality assessment is an integral stage in the processing and analysis of digital images in various automated systems. With the increase in the number and variety of devices that allow receiving data in various digital formats, as well as the expansion of human activities in which information technology (IT) is used, the need to assess the quality of the data obtained is growing. As well as the bar grows for the requirements for their quality.The article describes the factors that deteriorate the quality of digital images, areas of application of image quality assessment functions, a method fo

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Golub, Yu I., F. V. Starovoitov, and V. V. Starovoitov. "Impact of image size reducing for image quality assesment." «System analysis and applied information science», no. 2 (August 18, 2020): 35–45. http://dx.doi.org/10.21122/2309-4923-2020-2-35-45.

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The article describes studies of the effect of image reduction on the quantitative assessment of their quality. Image reduction refers to the proportional reduction of horizontal and vertical image resolutions in pixels. Within the framework of these studies, correlation analysis between quantitative assessments of image quality and subjective assessments of experts was performed. For the experiments, we used images from the public TID2013 database with a resolution of 512 × 384 pixels and expert estimates of their quality, as well as photographs taken with a Nikon D5000 digital camera with a

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Han, Z., X. Tang, X. Gao, and F. Hu. "IMAGE FUSION AND IMAGE QUALITY ASSESSMENT OF FUSED IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W1 (July 12, 2013): 33–36. http://dx.doi.org/10.5194/isprsarchives-xl-7-w1-33-2013.

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Starovoitov, V. V., Y. I. Golub, and M. M. Lukashevich. "Digital fundus image quality assessment." «System analysis and applied information science», no. 4 (January 5, 2022): 25–38. http://dx.doi.org/10.21122/2309-4923-2021-4-25-38.

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Diabetic retinopathy (DR) is a disease caused by complications of diabetes. It starts asymptomatically and can end in blindness. To detect it, doctors use special fundus cameras that allow them to register images of the retina in the visible range of the spectrum. On these images one can see features, which determine the presence of DR and its grade. Researchers around the world are developing systems for the automated analysis of fundus images. At present, the level of accuracy of classification of diseases caused by DR by systems based on machine learning is comparable to the level of qualif

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Li, Zhipeng, Li Shen, and Linmei Wu. "IMAGE QUATY ASSESSMENT FOR VHR REMOTE SENSING IMAGE CLASSIFICATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 17, 2016): 11–16. http://dx.doi.org/10.5194/isprs-archives-xli-b7-11-2016.

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The data from remote sensing images are widely used for characterizing land use and land cover at present. With the increasing availability of very high resolution (VHR) remote sensing images, the remote sensing image classification becomes more and more important for information extraction. The VHR remote sensing images are rich in details, but high within-class variance as well as low between-class variance make the classification of ground cover a difficult task. What’s more, some related studies show that the quality of VHR remote sensing images also has a great influence on the ability of

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Li, Zhipeng, Li Shen, and Linmei Wu. "IMAGE QUATY ASSESSMENT FOR VHR REMOTE SENSING IMAGE CLASSIFICATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 17, 2016): 11–16. http://dx.doi.org/10.5194/isprsarchives-xli-b7-11-2016.

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The data from remote sensing images are widely used for characterizing land use and land cover at present. With the increasing availability of very high resolution (VHR) remote sensing images, the remote sensing image classification becomes more and more important for information extraction. The VHR remote sensing images are rich in details, but high within-class variance as well as low between-class variance make the classification of ground cover a difficult task. What’s more, some related studies show that the quality of VHR remote sensing images also has a great influence on the ability of

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Patil, Varsha, Deepali Sale, and M. A. Joshi. "Image Fusion Methods and Quality Assessment Parameters." Asian Journal of Engineering and Applied Technology 2, no. 1 (2013): 40–45. http://dx.doi.org/10.51983/ajeat-2013.2.1.643.

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Image processing techniques primarily focus upon enhancing the quality of an image or a set of images and to derive the maximum information from them. Image Fusion is such a technique of producing a superior quality image from a set of available images. It is the process of combining relevant information from two or more images into a single image wherein the resulting image will be more informative and complete than any of the input images. A lot of research is being done in this field encompassing areas of Computer Vision, Automatic object detection, Image processing, parallel and distribute

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Boushey, C. J., M. Spoden, F. M. Zhu, E. J. Delp, and D. A. Kerr. "New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods." Proceedings of the Nutrition Society 76, no. 3 (2016): 283–94. http://dx.doi.org/10.1017/s0029665116002913.

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For nutrition practitioners and researchers, assessing dietary intake of children and adults with a high level of accuracy continues to be a challenge. Developments in mobile technologies have created a role for images in the assessment of dietary intake. The objective of this review was to examine peer-reviewed published papers covering development, evaluation and/or validation of image-assisted or image-based dietary assessment methods from December 2013 to January 2016. Images taken with handheld devices or wearable cameras have been used to assist traditional dietary assessment methods for

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Jamil, Sonain. "Review of Image Quality Assessment Methods for Compressed Images." Journal of Imaging 10, no. 5 (2024): 113. http://dx.doi.org/10.3390/jimaging10050113.

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The compression of images for efficient storage and transmission is crucial in handling large data volumes. Lossy image compression reduces storage needs but introduces perceptible distortions affected by content, compression levels, and display environments. Each compression method generates specific visual anomalies like blocking, blurring, or color shifts. Standardizing efficient lossy compression necessitates evaluating perceptual quality. Objective measurements offer speed and cost efficiency, while subjective assessments, despite their cost and time implications, remain the gold standard

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Wang, Mei, E. Ye Wang, and Guo Hua Pan. "Image Quality Assessment Based on Invariant Moments Similarity." Advanced Materials Research 546-547 (July 2012): 565–69. http://dx.doi.org/10.4028/www.scientific.net/amr.546-547.565.

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To resolve the problems of the image quality assessment issue and the algorithm adaptability for different image size and deformation, this paper proposes a image quality assessment algorithm based on Invariant Moments Similarity. Firstly, Hu invariant moments values of original image and evaluated image are computed. Secondly the invariant moments distance is completed between original image and evaluated image. At last, the method assess the restoration image quality depend on the invariant moment distance. The experimental result shows that the algorithm result is better than MSE, PSNR, SSI

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De, Kanjar, and Masilamani V. "NO-REFERENCE IMAGE QUALITY MEASURE FOR IMAGES WITH MULTIPLE DISTORTIONS USING RANDOM FORESTS FOR MULTI METHOD FUSION." Image Analysis & Stereology 37, no. 2 (2018): 105. http://dx.doi.org/10.5566/ias.1534.

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Over the years image quality assessment is one of the active area of research in image processing. Distortion in images can be caused by various sources like noise, blur, transmission channel errors, compression artifacts etc. Image distortions can occur during the image acquisition process (blur/noise), image compression (ringing and blocking artifacts) or during the transmission process. A single image can be distorted by multiple sources and assessing quality of such images is an extremely challenging task. The human visual system can easily identify image quality in such cases, but for a c

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Swarnkar, Santosh Kumar, and Prof Avinash Sharma. "Content-Based Image Retrieval: An Assessment." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (2019): 154–56. http://dx.doi.org/10.31142/ijtsrd21708.

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Jiao, Jichao, Wenyi Li, Zhongliang Deng, and Qasim Ali Arain. "A structural similarity-inspired performance assessment model for multisensor image registration algorithms." International Journal of Advanced Robotic Systems 14, no. 4 (2017): 172988141771705. http://dx.doi.org/10.1177/1729881417717059.

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In order to assess the performance of multisensor image registration algorithms that are used in the multirobot information fusion, we propose a model based on structural similarity whose name is vision registration assessment model. First of all, this article introduces a new image concept named superimposed image for testing subjective and objective assessment methods. Therefore, we assess the superimposed image but not the registered image, which is different from previous image registration assessment methods that usually use reference and sensed images. Then, we calculate eight assessment

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Fernandez-Maloigne, Christine, Jaime Moreno, Alessandro Rizzi, and Cristian Bonanomi. "QUALITAS: Image Quality Assessment for Stereoscopic Images." Color and Imaging Conference 2016, no. 1 (2016): 7–19. http://dx.doi.org/10.2352/issn.2169-2629.2017.32.7.

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Fernandez-Maloigne, Christine, Jaime Moreno, Alessandro Rizzi, and Cristian Bonanomi. "QUALITAS: Image Quality Assessment for Stereoscopic Images." Journal of Imaging Science and Technology 60, no. 5 (2016): 504051–5040513. http://dx.doi.org/10.2352/j.imagingsci.technol.2016.60.5.050405.

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Lee, Jino, and Rae-Hong Park. "Image Quality Assessment of Tone Mapped Images." International Journal of Computer Graphics & Animation 5, no. 2 (2015): 9–20. http://dx.doi.org/10.5121/ijcga.2015.5202.

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Berezsky, O. M., M. O. Berezkyi, M. O. Dombrovskyi, P. B. Liashchynskyi, and G. M. Melnyk. "COMBINED METRIC FOR EVALUATING THE QUALITY OF SYNTHESIZED BIOMEDICAL IMAGES." Radio Electronics, Computer Science, Control, no. 2 (June 29, 2025): 168–81. https://doi.org/10.15588/1607-3274-2025-2-15.

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Context. This study addresses the problem of developing a new metric for evaluating the quality of synthesized images. The relevance of this problem is explained by the need for assessing the quality of artificially generated images. Additionally, the study highlights the potential of biomedical image synthesis based on diffusion models. The research results can be applied for biomedical image generation and quantitative quality assessment of synthesized images.Objective. The aim of this study is to develop a combined metric and an algorithm for biomedical image synthesis to assess the quality

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Zhang, Lin, Xilin Yang, Lijun Zhang, Xiao Liu, Shengjie Zhao, and Yong Ma. "Towards Automatic Image Exposure Level Assessment." Mathematical Problems in Engineering 2020 (November 23, 2020): 1–14. http://dx.doi.org/10.1155/2020/2789854.

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The quality of acquired images can be surely reduced by improper exposures. Thus, in many vision-related industries, such as imaging sensor manufacturing and video surveillance, an approach that can routinely and accurately evaluate exposure levels of images is in urgent need. Taking an image as input, such a method is expected to output a scalar value, which can represent the overall perceptual exposure level of the examined image, ranging from extremely underexposed to extremely overexposed. However, studies focusing on image exposure level assessment (IELA) are quite sporadic. It should be

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Cruz, Domingos, Carla Valentí, Aureliano Dias, Mário Seixas, and Fernando Schmitt. "Digital Image Documentation for Quality Assessment." Archives of Pathology & Laboratory Medicine 125, no. 11 (2001): 1430–35. http://dx.doi.org/10.5858/2001-125-1430-didfqa.

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Abstract Objective.—To demonstrate the feasibility of the use of digital images to document routine cases and to perform diagnostic quality assessment. Methods.—Pathologists documented cases by acquiring up to 12 digital images per case. The images were sampled at 25:1, 50:1, 100:1, 200:1, or 400:1 magnifications, according to adequacy in aiding diagnosis. After each acquisition, the referral pathologist marked a region of interest within each acquired image in order to evaluate intrinsic redundancy. The extrinsic redundancy was determined by counting the unnecessary images. Cases were randoml

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Hamamoto, Kazuhiko. "STUDY ON OPTIMIZATION OF ARCHIVING CONDITION UNDER JPEG2000 AND ITS QUALITY EVALUATION FOR MEDICAL ULTRASONIC ECHO IMAGE." ASEAN Engineering Journal 1, no. 2 (2011): 40–50. http://dx.doi.org/10.11113/aej.v1.15289.

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Medical ultrasonic echo image is indispensable diagnostic technique and a large number of the investigation is carried out every day. Therefore, the image compression technique is very important. Author has proposed a technique using Genetic Algorithm (GA) to optimize quantization condition in JPEG2000. The result has shown image quality evaluation by PSNR (the objective assessment) and one by ultrasonographer (the subjective assessment by PSNR) are sometimes not equivalent. In this research, some objective assessment methods and the subjective assessment are compared for 4 images whose diseas

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Jiang, W., S. Chen, X. Wang, Q. Huang, H. Shi, and Y. Man. "REMOTE SENSING IMAGE QUALITY ASSESSMENT EXPERIMENT WITH POST-PROCESSING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 665–68. http://dx.doi.org/10.5194/isprs-archives-xlii-3-665-2018.

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This paper briefly describes the post-processing influence assessment experiment, the experiment includes three steps: the physical simulation, image processing, and image quality assessment. The physical simulation models sampled imaging system in laboratory, the imaging system parameters are tested, the digital image serving as image processing input are produced by this imaging system with the same imaging system parameters. The gathered optical sampled images with the tested imaging parameters are processed by 3 digital image processes, including calibration pre-processing, lossy compressi

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V. Karthikeyan and C. Jayanthi. "Improving image quality assessment with enhanced denoising autoencoders and optimization methods." Scientific Temper 15, spl-1 (2024): 132–40. https://doi.org/10.58414/scientifictemper.2024.15.spl.16.

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In the field of image quality assessment, effective noise reduction is critical for enhancing the perceptual quality of images and improving the accuracy of subsequent analyses. This study proposes an enhancement to denoising autoencoders (DAEs) through optimization techniques aimed at significantly improving image quality assessment outcomes. Traditional DAEs, while effective in reconstructing clean images from noisy inputs, can sometimes fail to adequately preserve intricate image details and structures, which are essential for quality evaluation. Our approach incorporates optimization strat

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Fante, Kinde Anlay, Fetulhak Abdurahman, and Mulugeta Tegegn Gemeda. "An Ingenious Application-Specific Quality Assessment Methods for Compressed Wireless Capsule Endoscopy Images." Transactions on Environment and Electrical Engineering 4, no. 1 (2020): 18. http://dx.doi.org/10.22149/teee.v4i1.139.

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<p>Image quality assessment methods are used in different image processing applications. Among them, image compression and image super-resolution can be mentioned in wireless capsule endoscopy (WCE) applications. The existing image compression algorithms for WCE employ the generalpurpose image quality assessment (IQA) methods to evaluate the quality of the compressed image. Due to the specific nature of the images captured by WCE, the general-purpose IQA methods are not optimal and give less correlated results to that of subjective IQA (visual perception). This paper presents improved im

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Le, Quyet-Tien, Patricia Ladret, Huu-Tuan Nguyen, and Alice Caplier. "Image Aesthetic Assessment Based on Image Classification and Region Segmentation." Journal of Imaging 7, no. 1 (2020): 3. http://dx.doi.org/10.3390/jimaging7010003.

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The main goal of this paper is to study Image Aesthetic Assessment (IAA) indicating images as high or low aesthetic. The main contributions concern three points. Firstly, following the idea that photos in different categories (human, flower, animal, landscape, …) are taken with different photographic rules, image aesthetic should be evaluated in a different way for each image category. Large field images and close-up images are two typical categories of images with opposite photographic rules so we want to investigate the intuition that prior Large field/Close-up Image Classification (LCIC) mi

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Saifeldeen, Abdalmajeed, Shu Hong Jiao, and Wei Liu. "Entirely Blind Image Quality Assessment Estimator." Applied Mechanics and Materials 543-547 (March 2014): 2496–99. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.2496.

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Prior knowledge about anticipated distortions and their corresponding human opinion scores is needed in the most general purpose no-reference image quality assessment algorithms. When creating the model, all distortion types may not be existed. Predicting the quality of distorted images in practical no-reference image quality assessment algorithms is devised without prior knowledge about images or their distortions. In this study, a blind/no-reference opinion and distortion unaware image quality assessment algorithm based on natural scenes is developed. The proposed approach uses a set of nove

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WANG, YUQING, MING ZHU, HAOCHEN PANG, and YONG WANG. "QUATERNION BASED COLOR IMAGE QUALITY ASSESSMENT INDEX." International Journal of Image and Graphics 11, no. 02 (2011): 195–206. http://dx.doi.org/10.1142/s0219467811004111.

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A quaternion model for describing color image is proposed in order to evaluate its quality. Local variance distribution of luminance layer is calculated. Color information is taken into account by using quaternion matrix. The description method is a combination of luminance layer and color information. The angle between the singular value feature vectors of the quaternion matrices corresponding to the reference image and the distorted image is used to measure the structural similarity of the two color images. When the reference image and distorted images are of unequal size it can also assess

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Yemul, Kiran S., Adam M. Zysk, Andrea L. Richardson, Krishnarao V. Tangella, and Lisa K. Jacobs. "Interpretation of Optical Coherence Tomography Images for Breast Tissue Assessment." Surgical Innovation 26, no. 1 (2018): 50–56. http://dx.doi.org/10.1177/1553350618803245.

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Purpose. Initial studies have shown that optical coherence tomography (OCT) is an effective margin-evaluation tool for breast-conserving surgery, but methods for the interpretation of breast OCT images have not been directly studied. In this work, breast pathologies were assessed with a handheld OCT probe. OCT images and corresponding histology were used to develop guidelines for the identification of breast tissue features in OCT images. Methods. Mastectomy and breast-conserving surgery specimens from 26 women were imaged with a handheld OCT probe. During standard pathology specimen dissectio

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Zhai, Guangtao, Wei Sun, Xiongkuo Min, and Jiantao Zhou. "Perceptual Quality Assessment of Low-light Image Enhancement." ACM Transactions on Multimedia Computing, Communications, and Applications 17, no. 4 (2021): 1–24. http://dx.doi.org/10.1145/3457905.

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Low-light image enhancement algorithms (LIEA) can light up images captured in dark or back-lighting conditions. However, LIEA may introduce various distortions such as structure damage, color shift, and noise into the enhanced images. Despite various LIEAs proposed in the literature, few efforts have been made to study the quality evaluation of low-light enhancement. In this article, we make one of the first attempts to investigate the quality assessment problem of low-light image enhancement. To facilitate the study of objective image quality assessment (IQA), we first build a large-scale low

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Attia, Salim J. "Assessment of Some Enhancement Methods of Renal X-ray Image." NeuroQuantology 18, no. 12 (2020): 01–05. http://dx.doi.org/10.14704/nq.2020.18.12.nq20231.

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The study focuses on assessment of the quality of some image enhancement methods which were implemented on renal X-ray images. The enhancement methods included Imadjust, Histogram Equalization (HE) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The images qualities were calculated to compare input images with output images from these three enhancement techniques. An eight renal x-ray images are collected to perform these methods. Generally, the x-ray images are lack of contrast and low in radiation dosage. This lack of image quality can be amended by enhancement process. Three q

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Agudelo-Medina, Oscar A., Hernan Dario Benitez-Restrepo, Gemine Vivone, and Alan Bovik. "Perceptual Quality Assessment of Pan-Sharpened Images." Remote Sensing 11, no. 7 (2019): 877. http://dx.doi.org/10.3390/rs11070877.

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Pan-sharpening (PS) is a method of fusing the spatial details of a high-resolution panchromatic (PAN) image with the spectral information of a low-resolution multi-spectral (MS) image. Visual inspection is a crucial step in the evaluation of fused products whose subjectivity renders the assessment of pansharpened data a challenging problem. Most previous research on the development of PS algorithms has only superficially addressed the issue of qualitative evaluation, generally by depicting visual representations of the fused images. Hence, it is highly desirable to be able to predict pan-sharp

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Jermain, Peter R., Tyler W. Iorizzo, Mary Maloney, Bassel Mahmoud, and Anna N. Yaroslavsky. "Design and Validation of a Handheld Optical Polarization Imager for Preoperative Delineation of Basal Cell Carcinoma." Cancers 14, no. 16 (2022): 4049. http://dx.doi.org/10.3390/cancers14164049.

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Background: Accurate removal of basal cell carcinoma (BCC) is challenging due to the subtle contrast between cancerous and normal skin. A method aiding with preoperative delineation of BCC margins would be valuable. The aim of this study was to implement and clinically validate a novel handheld optical polarization imaging (OPI) device for rapid, noninvasive, in vivo assessment of skin cancer margins. Methods: The handheld imager was designed, built, and tested. For clinical validation, 10 subjects with biopsy-confirmed BCC were imaged. Presumable cancer margins were marked by the study surgeo

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Besprozvannaya, I. I., and A. V. Zhegallo. "The structure of ideas about yourself and others (according to a photographic image and a schematic image)." Experimental Psychology (Russia) 12, no. 3 (2019): 19–27. http://dx.doi.org/10.17759/exppsy.2019120302.

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The participants in the study assessed themselves according to the “personal differential” questionnaire and also performed the evaluation of the other using photo images or graphic schemes. When performing a self-assessment and evaluation of another in a photo image, the three-factor structure described by the authors of the methodology is mainly reproduced: “assessment”, strength ”,“ activity ”. The structure of assessments of another according to the schematic image is substantially different from the classical one, which indicates the fundamental differences in the perception of individual

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Liu, Xiaoyu, Shirley J. Dyke, Chul Min Yeum, Ilias Bilionis, Ali Lenjani, and Jongseong Choi. "Automated Indoor Image Localization to Support a Post-Event Building Assessment." Sensors 20, no. 6 (2020): 1610. http://dx.doi.org/10.3390/s20061610.

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Image data remains an important tool for post-event building assessment and documentation. After each natural hazard event, significant efforts are made by teams of engineers to visit the affected regions and collect useful image data. In general, a global positioning system (GPS) can provide useful spatial information for localizing image data. However, it is challenging to collect such information when images are captured in places where GPS signals are weak or interrupted, such as the indoor spaces of buildings. The inability to document the images’ locations hinders the analysis, organizat

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Varga, Domonkos. "Saliency-Guided Local Full-Reference Image Quality Assessment." Signals 3, no. 3 (2022): 483–96. http://dx.doi.org/10.3390/signals3030028.

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Research and development of image quality assessment (IQA) algorithms have been in the focus of the computer vision and image processing community for decades. The intent of IQA methods is to estimate the perceptual quality of digital images correlating as high as possible with human judgements. Full-reference image quality assessment algorithms, which have full access to the distortion-free images, usually contain two phases: local image quality estimation and pooling. Previous works have utilized visual saliency in the final pooling stage. In addition to this, visual saliency was utilized as

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Zhang, Yin, Xuehan Bai, Junhua Yan, et al. "A Full-Reference Image Quality Assessment for Multiply Distorted Image based on Visual Mutual Information." Journal of Imaging Science and Technology 63, no. 6 (2019): 60504–1. http://dx.doi.org/10.2352/j.imagingsci.technol.2019.63.6.060504.

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Abstract A full-reference image quality assessment (FR-IQA) method for multi-distortion based on visual mutual information (MD-IQA) is proposed to solve the problem that the existing FR-IQA methods are mostly applicable to single-distorted images, but the assessment result for multiply distorted images is not ideal. First, the reference image and the distorted image are preprocessed by steerable pyramid decomposition and contrast sensitivity function (CSF). Next, a Gaussian scale mixture (GSM) model and an image distorted model are respectively constructed for the reference images and the dist

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Wang, Dingxian. "Edge Detection technique based on HDR image quality assessment." Journal of Physics: Conference Series 2078, no. 1 (2021): 012029. http://dx.doi.org/10.1088/1742-6596/2078/1/012029.

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Abstract Image edge detection is one of the major study aspects in current computer image processing field. The quality of the input images is uneven, some have large fuzzy areas, some are underexposed, and the edges of objects in the images are difficult to detect, and the application scenarios of image edge detection are limited. In the view of the above problems, this paper has proposed that by applying High Dynamic Range (HDR) image quality assessment technology, combining multiple images with different exposures into one HDR image with detailed edge information, This technology effectivel

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Song, Zengjie, Jiangshe Zhang, and Junmin Liu. "No-Reference Image Quality Assessment Using Image Saliency for JPEG Compressed Images." Journal of Imaging Science and Technology 60, no. 6 (2016): 605031–38. http://dx.doi.org/10.2352/j.imagingsci.technol.2016.60.6.060503.

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Guo, Ming Wei, Chen Bin Zhang, and Zong Hai Chen. "A Novel Method of Image Quality Assessment." Applied Mechanics and Materials 556-562 (May 2014): 5064–67. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.5064.

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Image quality assessment (IQA) is one of the hot research areas in the field of image processing. For the reason that human being is the final receiver of the image, the image quality assessment should match the characteristics of human visual system. In this paper, we propose a novel method of image quality assessment which uses the visual selective attention of human visual system. For an image of a certain category, our method firstly detects the object in it and then calculate the saliency of the object. Lastly we use the combination of the detector’s score and the saliency as the image qu

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Anikeeva, I., and A. Chibunichev. "RANDOM NOISE ASSESSMENT IN AERIAL AND SATELLITE IMAGES." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2021 (June 28, 2021): 771–75. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2021-771-2021.

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Abstract. Random noise in aerial and satellite images is one of the factors, decreasing their quality. The noise level assessment in images is paid not enough attention. The method of numerical estimation of random image noise is considered. The object of the study is the image noise estimating method, based on harmonic analysis. The capability of using this method for aerial and satellite image quality assessment is considered. The results of the algorithm testing on model data and on real satellite images with different terrain surfaces are carried out. The accuracy estimating results for ca

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CM, Sushmitha, and Meharunnisa SP. "An Image Quality Assessment of Multi-Exposure Image Fusion by Improving SSIM." International Journal of Trend in Scientific Research and Development Volume-2, Issue-4 (2018): 2780–84. http://dx.doi.org/10.31142/ijtsrd15634.

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Thomas, Deepa Maria, and S. John Livingston. "A Novel Hybrid Image Quality Assessment Algorithm." Indian Journal of Applied Research 4, no. 4 (2011): 107–8. http://dx.doi.org/10.15373/2249555x/apr2014/31.

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Ruikar, Jayesh, Ashoke Sinha, and Saurabh Chaudhury. "Image Quality Assessment Using Edge Correlation." International Journal of Electronics and Telecommunications 63, no. 1 (2017): 99–107. http://dx.doi.org/10.1515/eletel-2017-0014.

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Abstract In literature, oriented filters are used for low-level vision tasks. In this paper, we propose use of steerable Gaussian filter in image quality assessment. Human visual system is more sensitive to multidirectional edges present in natural images. The most degradation in image quality is caused due to its edges. In this work, an edge based metric termed as steerable Gaussian filtering (SGF) quality index is proposed as objective measure for image quality assessment. The performance of the proposed technique is evaluated over multiple databases. The experimental result shows that propo

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Zhang, Siyuan, Yifan Wang, Jiayao Jiang, Jingxian Dong, Weiwei Yi, and Wenguang Hou. "CNN-Based Medical Ultrasound Image Quality Assessment." Complexity 2021 (July 1, 2021): 1–9. http://dx.doi.org/10.1155/2021/9938367.

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The quality of ultrasound image is a key information in medical related application. It is also an important index in evaluating the performance of ultrasonic imaging equipment and image processing algorithms. Yet, there is still no recognized quantitative standard about medical image quality assessment (IQA) due to the fact that IQA is traditionally regarded as a subjective issue, especially in case of the ultrasound medical images. As such, the medical ultrasound IQA on basis of convolutional neural network (CNN) is quantitatively studied in this paper. Firstly, a dataset with 1063 ultrasoun

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Feng, C., D. Yu, Y. Liang, D. Guo, Q. Wang, and X. Cui. "ASSESSMENT OF INFLUENCE OF IMAGE PROCESSING ON FULLY AUTOMATIC UAV PHOTOGRAMMETRY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 4, 2019): 269–75. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-269-2019.

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<p><strong>Abstract.</strong> Nowadays UAVs have been widely used for large scale surveying and mapping. Compared with traditional surveying techniques, UAV photogrammetry is more convenient, cost-effective, and responsive. Aerial images, Position and Orientation System (POS) observations and coordinates of ground control points are usually acquired during a surveying campaign. Aerial images are the data source of feature point extraction, dense matching and ortho-rectification procedures. The quality of the images is one of the most important factors that influence the accur

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Golub, Y. I., and F. V. Starovoitov. "Digital image contrast assessment based on the Weibull distribution parameters." «System analysis and applied information science», no. 2 (August 19, 2021): 4–13. http://dx.doi.org/10.21122/2309-4923-2021-2-4-13.

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The goal of the studies described in the paper is to find a quantitative assessment that maximally correlates with the subjective assessment of the contrast image quality in the absence of reference image. As a result of the literature analysis, 16 functions were selected that are used for no-refernce image quality assessment: BEGH, BISH, BREN, CMO, CURV, FUS, HELM, EBCM, KURT, LAPD, LAPL, LAPM, LOCC, LOEN, SHAR, WAVS. They all use the arithmetical mean of the local contrast quality. As an alternative to averaging local estimates (since the mean is one of two parameters of the normal distribut

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Ayyanna, K. "Image Quality Assessment for Multi Exposure Fused Images." International Journal for Research in Applied Science and Engineering Technology V, no. III (2017): 990–96. http://dx.doi.org/10.22214/ijraset.2017.3182.

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Zhang, Chen, Wu Cheng, and Keigo Hirakawa. "Corrupted Reference Image Quality Assessment of Denoised Images." IEEE Transactions on Image Processing 28, no. 4 (2019): 1732–47. http://dx.doi.org/10.1109/tip.2018.2878326.

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Wang, Zhiyu, Jiayan Zhuang, Sichao Ye, Ningyuan Xu, Jiangjian Xiao, and Chengbin Peng. "Image Restoration Quality Assessment Based on Regional Differential Information Entropy." Entropy 25, no. 1 (2023): 144. http://dx.doi.org/10.3390/e25010144.

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With the development of image recovery models, especially those based on adversarial and perceptual losses, the detailed texture portions of images are being recovered more naturally. However, these restored images are similar but not identical in detail texture to their reference images. With traditional image quality assessment methods, results with better subjective perceived quality often score lower in objective scoring. Assessment methods suffer from subjective and objective inconsistencies. This paper proposes a regional differential information entropy (RDIE) method for image quality a

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Zhang, Jiexin, Jianjiang Zhou, Minglei Li, Huiyu Zhou, and Tianzhu Yu. "Quality Assessment of SAR-to-Optical Image Translation." Remote Sensing 12, no. 21 (2020): 3472. http://dx.doi.org/10.3390/rs12213472.

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Synthetic aperture radar (SAR) images contain severe speckle noise and weak texture, which are unsuitable for visual interpretation. Many studies have been undertaken so far toward exploring the use of SAR-to-optical image translation to obtain near optical representations. However, how to evaluate the translation quality is a challenge. In this paper, we combine image quality assessment (IQA) with SAR-to-optical image translation to pursue a suitable evaluation approach. Firstly, several machine-learning baselines for SAR-to-optical image translation are established and evaluated. Then, exten

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Zhang, Chun E., Fan Ci Guo, and Ke Xiong. "Towards Subjective Consistency: An Effective Objective Quality Assessment Algorithm for Binary Image." Key Engineering Materials 474-476 (April 2011): 143–50. http://dx.doi.org/10.4028/www.scientific.net/kem.474-476.143.

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Image quality assessment plays an important role in various image processing applications. One of the challenges to objectively assess image quality is how to design an effective scheme to achieve high consistency with the classic subjective image assessment criterion, Mean Opinion Score (MOS). This work presents a novel objective assessment algorithm for binary images by considering three factors which have great influences on visual quality of binary images, i.e., structural change caused by noise point, isolated noise points, and gathering noise points. Experimental results show that our al

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