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Relevant bibliographies by topics / Algorithm for image processing

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Academic literature on the topic 'Algorithm for image processing'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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Journal articles on the topic "Algorithm for image processing"

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Лун, Сюй, Xu Long, Йан Йихуа, Yan Yihua, Чэн Цзюнь, and Cheng Jun. "Guided filtering for solar image/video processing." Solar-Terrestrial Physics 3, no. 2 (2017): 9–15. http://dx.doi.org/10.12737/stp-3220172.

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A new image enhancement algorithm employing guided filtering is proposed in this work for enhancement of solar images and videos, so that users can easily figure out important fine structures imbedded in the recorded images/movies for solar observation. The proposed algorithm can efficiently remove image noises, including Gaussian and impulse noises. Meanwhile, it can further highlight fibrous structures on/beyond the solar disk. These fibrous structures can clearly demonstrate the progress of solar flare, prominence coronal mass emission, magnetic field, and so on. The experimental results pr

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Kusnadi, Adhi, Leondy ., Lianna Nathania, Ivransa Zuhdi Pane, Marlinda Vasty Overbeek, and Syarief Gerald Prasetya. "Image Processing for Improvement of Facial Keypoints Detector." Webology 19, no. 1 (2022): 676–91. http://dx.doi.org/10.14704/web/v19i1/web19048.

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This paper discusses the improvement of facial detection algorithms using the DCT algorithm and image processing. Face key point is very needed in the face recognition system. Some important factors that have effects to detect its result are noise and illuminations. These two factors can be overcome by eliminating some DCT coefficients, both high and low. However, after handling the problem, most likely the image quality will become decrease, which will adversely influence the performance of the feature detector algorithm. Therefore, it is very important to test the performance of the feature

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Hou, Maowen. "Image Processing Based on Fuzzy Mathematics Theory." Security and Communication Networks 2022 (August 22, 2022): 1–10. http://dx.doi.org/10.1155/2022/5287025.

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In order to further improve the problems of poor rationality and weak antinoise ability of existing image processing algorithms and technical algorithms, an image processing research method based on fuzzy mathematical theory is proposed. First, aiming at the ill-posed problem of the PFCM algorithm, the neutrality and rejection degree are used to construct a regular term and embed the algorithm objective function to enhance the correlation between the attribute parameters of the fuzzy set of the sample graph, so as to solve the ill-posed problem of the PFCM algorithm. Secondly, in view of the s

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Лун, Сюй, Xu Long, Йан Йихуа, Yan Yihua, Чэн Цзюнь, and Cheng Jun. "Guided filtering for solar image/video processing." Solnechno-Zemnaya Fizika 3, no. 2 (2017): 10–17. http://dx.doi.org/10.12737/22596.

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A new image enhancement algorithm employing guided filtering is proposed in this work for enhancement of solar images and videos, so that users can easily figure out important fine structures imbedded in the recorded images/movies for solar observation. The proposed algorithm can efficiently remove image noises, including Gaussian and impulse noises. Meanwhile, it can further highlight fibrous structures on/beyond the solar disk. These fibrous structures can clearly demonstrate the progress of solar flare, prominence coronal mass emission, magnetic field, and so on. The experimental results pr

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Wang, Wencheng, Quandi Wu, Fa Huang, Guoqing Cai, and Lijie Zhou. "Analysis of Image Processing Algorithms for Water Surface Garbage Cleaning Robots." Academic Journal of Science and Technology 10, no. 1 (2024): 12–15. http://dx.doi.org/10.54097/j9hj0665.

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To facilitate the observation of the water surface conditions in front of the water surface garbage cleaning robots during navigation, an image transmission function was designed using cameras and wireless transmission equipment. However, due to the influence of water surface lighting, the transmitted images were unclear. In this paper, five image processing algorithms were written in Python language using the OpenCV library: Histogram Equalization, Gray World Algorithm, Retinex-based Enhancement Algorithm, Automatic White Balance (AWB) Algorithm, and Automatic Color Equalization (ACE) Algorit

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Chaudhary, Sunita. "An Efficient Medical Image Processing Approach Based on a Cognitive Marine Predators Algorithm." International Journal on Future Revolution in Computer Science & Communication Engineering 8, no. 1 (2022): 08–14. http://dx.doi.org/10.17762/ijfrcsce.v8i1.2084.

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Image processing aims to enhance the image's quality such that it is simple for both people and robots to understand. Medical image processing and Biomedical signal processing have many conceptual similarities. Medical image processing involves evaluation, enhancement, and presentation. The focus of medical imaging is on obtaining photographs for both therapeutic and diagnostic reasons. In the existing Marine Predator Algorithm, different disadvantages are experienced when various automated optimization algorithms are used to the problem of ECG categorization. The proposed method follows the f

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Chen, Mujun. "Automatic Image Processing Algorithm for Light Environment Optimization Based on Multimodal Neural Network Model." Computational Intelligence and Neuroscience 2022 (June 3, 2022): 1–12. http://dx.doi.org/10.1155/2022/5156532.

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In this paper, we conduct an in-depth study and analysis of the automatic image processing algorithm based on a multimodal Recurrent Neural Network (m-RNN) for light environment optimization. By analyzing the structure of m-RNN and combining the current research frontiers of image processing and natural language processing, we find out the problem of the ineffectiveness of m-RNN for some image generation descriptions, starting from both the image feature extraction part and text sequence data processing. Unlike traditional image automatic processing algorithms, this algorithm does not need to

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Hua, Jiyong, Hongmei Yin, Zhijun Li, Shaojun Wang, and Chen Chen. "Algorithm for Enhancing the Resolution of Workshop Part Images." Journal of Physics: Conference Series 2617, no. 1 (2023): 012008. http://dx.doi.org/10.1088/1742-6596/2617/1/012008.

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Abstract The resolution of the input image will affect the restoration effect of the image. In a fixed environment, obtaining high-quality images requires expensive acquisition devices, such as cameras. There are many ways to improve image quality. Instead of increasing hardware investment, it is better to find methods in image post-processing. Deep learning algorithms have obvious advantages in image processing. Based on deep learning, we propose an algorithm to convert camera captured images into high-resolution images. VDSR (Very Accurate Super Resolution) is a typical algorithm. Use residu

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Soundarya, B. A., D. Sowmeya, and G. V. Yazhini. "Visual Cryptography for Image Processing A Survey." International Journal of Trend in Scientific Research and Development 2, no. 1 (2017): 1417–21. https://doi.org/10.31142/ijtsrd8206.

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The method in which the visual information is encrypted by the process of encryption and those encrypted images are decrypted via sight reading is said to be called as visual cryptography or it is a method to hide the picture or an image into non identical number of shares different shares and they are distributed to different set of participants. There are two sets of participants namely qualified and unqualified. The qualified set will combine with the participants of non qualified set in order to get the secret image. Or the qualified set of participants alone can get the secret image. This

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Poddubnyi, Vadym, Oleksandr Sievierinov, and Dmytro Nepokrytov. "Research the efficiency of image processing algorithms in zero watermark schemes." INNOVATIVE TECHNOLOGIES AND SCIENTIFIC SOLUTIONS FOR INDUSTRIES, no. 1(31) (March 31, 2025): 102–14. https://doi.org/10.30837/2522-9818.2025.1.102.

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Subject matter: image transformation algorithms used in zero-watermarking techniques for development authentication algorithm. Objectives: identify effective image transformation algorithms for use in zero-watermarking schemes. The study addresses the following tasks: examining the range of existing image transformation algorithms, formulating informal requirements for image transformation algorithms to be used in zero-watermarking-based authentication schemes, and making assumptions about the feasibility of using each analyzed image transformation algorithm. To achieve these objectives, the f

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Dissertations / Theses on the topic "Algorithm for image processing"

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Harp, J. G. "Algorithms and architectures for image processing." Thesis, University of Surrey, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.379431.

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Mahmoudi, Ramzi, and Ramzi Mahmoudi. "Real time image processing : algorithm parallelization on multicore multithread architecture." Phd thesis, Université Paris-Est, 2011. http://pastel.archives-ouvertes.fr/pastel-00680735.

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Topological features of an object are fundamental in image processing. In many applications,including medical imaging, it is important to maintain or control the topology of the image. Howeverthe design of such transformations that preserve topology and geometric characteristics of the inputimage is a complex task, especially in the case of parallel processing.Parallel processing is applied to accelerate computation by sharing the workload among multipleprocessors. In terms of algorithm design, parallel computing strategies profits from the naturalparallelism (called also partial order of algo

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Greenaway, Richard Scott. "Image processing and data analysis algorithm for application in haemocytometry." Thesis, University of Hertfordshire, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263063.

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Mahmoudi, Ramzi. "Real time image processing : algorithm parallelization on multicore multithread architecture." Thesis, Paris Est, 2011. http://www.theses.fr/2011PEST1033/document.

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Les caractéristiques topologiques d'un objet sont fondamentales dans le traitement d'image. Dansplusieurs applications, notamment l'imagerie médicale, il est important de préserver ou de contrôlerla topologie de l'image. Cependant la conception de telles transformations qui préservent à la foi la topologie et les caractéristiques géométriques de l'image est une tache complexe, en particulier dans le cas du traitement parallèle.Le principal objectif du traitement parallèle est d'accélérer le calcul en partagent la charge de travail à réaliser entre plusieurs processeurs. Si on approche cet obje

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Flores, Daniel. "Evaluation of an image processing algorithm for scene change detection." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2008. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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Manfredsson, Johan. "Evaluation Tool for a Road Surface Algorithm." Thesis, Linköpings universitet, Datorseende, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138936.

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Modern cars are often equipped with sensors like radar, infrared cameras and stereo cameras that collect information about its surroundings. By using a stereo camera, it is possible to receive information about the distance to points in front of the car. This information can be used to estimate the height of the predicted path of the car. An application which does this is the stereo based Road surface preview (RSP) algorithm. By using the output from the RSP algorithm it is possible to use active suspension control, which controls the vertical movement of the wheels relative to the chassis. Th

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Groder, Seth. "Modeling and synthesis of the HD photo compression algorithm /." Online version of thesis, 2008. http://hdl.handle.net/1850/7118.

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Shajahan, Sunoj. "Agricultural Field Applications of Digital Image Processing Using an Open Source ImageJ Platform." Diss., North Dakota State University, 2019. https://hdl.handle.net/10365/29711.

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Digital image processing is one of the potential technologies used in precision agriculture to gather information, such as seed emergence, plant health, and phenology from the digital images. Despite its potential, the rate of adoption is slow due to limited accessibility, unsuitability to specific issues, unaffordability, and high technical knowledge requirement from the clientele. Therefore, the development of open source image processing applications that are task-specific, easy-to-use, requiring fewer inputs, and rich with features will be beneficial to the users/farmers for adoption. The

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He, Zhijun. "System And Algorithm Design For Varve Image Analysis System." Diss., The University of Arizona, 2007. http://hdl.handle.net/10150/196015.

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This dissertation describes the design and implementation of a computer vision based varve image analysis system. The primary issues covered are software engineering design, varve image calibrations, varve image enhancement, varve Dynamic Spatial Warping (DSW) profile generation, varve core image registration, varve identification, boundary identification and varve thickness measurement. A varve DSW matching algorithm is described to generate DSW profile and register two core images. Wavelet Multiple Resolution Analysis (MRA) is also used to do the core image registrations. By allowing an ana

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Hu, Nan. "SECURE IMAGE PROCESSING." UKnowledge, 2007. http://uknowledge.uky.edu/gradschool_theses/448.

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In todays heterogeneous network environment, there is a growing demand for distrusted parties to jointly execute distributed algorithms on private data whose secrecy needed to be safeguarded. Platforms that support such computation on image processing purposes are called secure image processing protocols. In this thesis, we propose a new security model, called quasi information theoretic (QIT) security. Under the proposed model efficient protocols on two basic image processing algorithms linear filtering and thresholding are developed. For both problems we consider two situations: 1) only tw

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Books on the topic "Algorithm for image processing"

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Gogniat, Guy, Dragomir Milojevic, Adam Morawiec, and Ahmet Erdogan, eds. Algorithm-Architecture Matching for Signal and Image Processing. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-9965-5.

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Moayeri, Nader. An algorithm for blind restoration of blurred and noisy images. Hewlett-Packard Laboratories, Technical Publications Department, 1996.

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P, DeFigueiredo Rui J., Krishen Kumar, and United States. National Aeronautics and Space Administration., eds. Formulation and error analysis for a generalized image point correspondence algorithm. Academic Press, Inc., 1992.

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P, DeFigueiredo Rui J., Krishen Kumar, and United States. National Aeronautics and Space Administration., eds. Formulation and error analysis for a generalized image point correspondence algorithm. Academic Press, Inc., 1992.

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Kovalevsky, Vladimir. Modern Algorithms for Image Processing. Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-4237-7.

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I, Pitas, ed. 3-D image processing algorithms. John Wiley, 2001.

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Safonov, Ilia V., Ilya V. Kurilin, Michael N. Rychagov, and Ekaterina V. Tolstaya. Adaptive Image Processing Algorithms for Printing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-6931-4.

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Sid-Ahmed, Maher A. Image processing: Theory, algorithms, and architectures. McGraw-Hill, 1995.

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Yung, Kong T., and Rosenfeld Azriel 1931-, eds. Topological algorithms for digital image processing. Elsevier, 1996.

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1958-, Wu Qiang, Merchant Fatima, and Castleman Kenneth R, eds. Microscope image processing. Academic Press, 2008.

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Book chapters on the topic "Algorithm for image processing"

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Wang, Gai-Ge, Xiaoqi Zhao, and Keqin Li. "Image Processing." In Metaheuristic Algorithms. CRC Press, 2024. http://dx.doi.org/10.1201/9781003422426-11.

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Toriwaki, Junichiro, and Hiro Yoshida. "Algorithm Of Binary Image Processing." In Fundamentals of Three-Dimensional Digital Image Processing. Springer London, 2009. http://dx.doi.org/10.1007/978-1-84800-173-2_5.

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Cross, A. D. J., and E. R. Hancock. "Perspective matching using the EM algorithm." In Image Analysis and Processing. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63507-6_226.

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Masulli, F., M. Straforini, and G. Sandini. "A Stereo Algorithm for Flat Objects." In Image Analysis and Processing. Springer US, 1986. http://dx.doi.org/10.1007/978-1-4613-2239-9_13.

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Oliva, Diego, Mohamed Abd Elaziz, and Salvador Hinojosa. "Image Processing." In Metaheuristic Algorithms for Image Segmentation: Theory and Applications. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12931-6_4.

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Fernàndez, G., M. Kunt, and J. P. Zrÿd. "A new plant cell image segmentation algorithm." In Image Analysis and Processing. Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-60298-4_263.

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Oddy, C. J., and J. R. M. Mason. "Image Processing Algorithms." In The Impact of Processing Techniques on Communications. Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5113-6_32.

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Jonker, Petrus Paulus. "Image processing algorithms." In Morphological Image Processing: Architecture and VLSI design. Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-2804-3_2.

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Bajcsy, Peter, Joe Chalfoun, and Mylene Simon. "Image Processing Algorithms." In Web Microanalysis of Big Image Data. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-63360-2_5.

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Trivedi, Deven N., Nimit D. Shah, Ashish M. Kothari, and Rohit M. Thanki. "Analytical Study of Edge Detection Algorithms and Contouring Algorithm." In Dental Image Processing for Human Identification. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-99471-0_3.

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Conference papers on the topic "Algorithm for image processing"

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Zhang, Zeyu, Huiyu Duan, Guangtao Zhai, Bo Jiang, and Yuye Ling. "Video inspired lesion segmentation algorithm for OCT retinal images." In Image Processing, edited by Olivier Colliot and Jhimli Mitra. SPIE, 2025. https://doi.org/10.1117/12.3047184.

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Overmeyer, Austin. "A Rotor Tip Vortex Tracing Algorithm for Image Post-Processing." In Vertical Flight Society 71st Annual Forum & Technology Display. The Vertical Flight Society, 2015. http://dx.doi.org/10.4050/f-0071-2015-10278.

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A neurite tracing algorithm, originally developed for medical image processing, was used to trace the location of the rotor tip vortex in density gradient flow visualization images. The tracing algorithm was applied to several representative test images to form case studies. The accuracy of the tracing algorithm was compared to two current methods including a manual point and click method and a cross-correlation template method. It is shown that the neurite tracing algorithm can reduce the post-processing time to trace the vortex by a factor of 10 to 15 without compromising the accuracy of the

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Turgunov, Abrorjon M., Temur N. Narzullaev, Marks Ya Matyakubov, Munira T. Payzieva, Sevara J. Kamolova, and Nilufar N. Rakhmonova. "Fuzzy Morphological Processing Algorithm of Blood Image." In 2024 IEEE 25th International Conference of Young Professionals in Electron Devices and Materials (EDM). IEEE, 2024. http://dx.doi.org/10.1109/edm61683.2024.10615208.

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K, Thilagavathi, Aldrick Peter T, Hariram TS, et al. "Image Pixelization Using Image Processing Algorithms." In 2025 3rd International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA). IEEE, 2025. https://doi.org/10.1109/icaeca63854.2025.11012246.

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Princye, P. Hosanna, and Suzain Mehak. "Brain Tumor Detection Using Image Processing." In International Conference on Recent Trends in Computing & Communication Technologies (ICRCCT’2K24). International Journal of Advanced Trends in Engineering and Management, 2024. http://dx.doi.org/10.59544/itqb1258/icrcct24p112.

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This proposed work presents an innovative artificial intelligence (AI) based algorithm for the accurate identification of brain tumors through medical imaging analysis. Brain tumors pose a significant health risk, and timely and precise diagnosis is crucial for effective treatment planning. Traditional diagnostic methods often require extensive manual analysis and are subject to human error. In this context, our proposed algorithm leverages the capabilities of deep learning and image processing to enhance the efficiency and accuracy of brain tumor identification. The algorithm utilizes a convo

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SEO, JUNWON, EUISEOK JEONG, and JAMES P. WACKER. "UAS INSPECTION IMAGE ENHANCEMENT COUPLED WITH DENOISE ALGORITHM BASED ON DEEP NEURAL NETWORK." In Structural Health Monitoring 2021. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/shm2021/36333.

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Unmanned Aerial System (UAS) technologies integrated with image processing algorithms are considered timely and useful for bridge inspections because of improved accessibility, recording ability, and cost-efficiency compared to the conventional inspection approach. The image processing algorithms can improve the ability of the UAS-aided bridge inspections in efficiently identifying and quantifying deterioration. This study was aimed to inspect an in-service single-span precast concrete bridge on a rural roadway in South Dakota using UAS technologies coupled with a Deep Neural Network (DNN) den

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Xu, Dong, Tian Liu, Zhengyang Zhou, et al. "A denoising algorithm for CT image using low-rank sparse coding." In Image Processing, edited by Elsa D. Angelini and Bennett A. Landman. SPIE, 2018. http://dx.doi.org/10.1117/12.2292890.

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Alsam, Ali, and Hans Jakob Rivertz. "Fast Edge Preserving Smoothing Algorithm." In Signal and Image Processing. ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.759-025.

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Alsam, Ali, and Hans Jakob Rivertz. "Fast Edge Preserving Smoothing Algorithm." In Signal and Image Processing. ACTAPRESS, 2012. http://dx.doi.org/10.2316/p.2012.759-025.

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Halyo, Nesim, and Richard W. Samms. "Combined Optimization of Image Gathering Optics and Image Processing Algorithm for Edge Detection." In Machine Vision. Optica Publishing Group, 1985. http://dx.doi.org/10.1364/mv.1985.thd1.

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Much attention on edge detection has centered around the development of algorithms which process the sampled image data obtained by an image acquisition system [1]. While considerable work on designing (general-purpose) image gathering optics also exists the interrelationships between the two design processes has received little attention. This paper formulates a combined stochastic optimization problem where the optical transfer function (OTF) of the image gathering optics, the sampling lattice, the noise level and the image processing algorithm are all design parameters to be selected accord

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Reports on the topic "Algorithm for image processing"

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George, Nicholas, and David M. Berfanger. Halftoning and Image Processing Algorithms. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada369915.

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Fedkiw, Ron. Algorithm Design for Computational Fluid Dynamics, Scientific Visualization, and Image Processing. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada461529.

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Sun, Xiaobai, and Nikos P. Pitsianis. FANTOM: Algorithm-Architecture Codesign for High-Performance Embedded Signal and Image Processing Systems. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada581464.

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Schoening, Timm. OceanCV. GEOMAR, 2022. http://dx.doi.org/10.3289/sw_5_2022.

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OceanCV provides computer vision algorithms and tools for underwater image analysis. This includes image processing, pattern recognition, machine learning and geometric algorithms but also functionality for navigation data processing, data provenance etc.

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Stevenson, Robert L., Andrew Lumsdaine, Jeffery M. Squires, and Micheal P. McNally. Parallel and Distributed Algorithms for High-Speed Image Processing. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada377689.

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Lehman, S. K. IDP++: signal and image processing algorithms in C++ version 4.1. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/461375.

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DeVore, Ronald A., and Pencho Petrushev. Highly Nonlinear Algorithms for Wavelet Based Image Processing With Military Applications. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada391704.

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Monical, Cara, Phillip Lewis, Abrielle Agron, Kurt Larson, and Andrew Mounce. Image Processing Algorithms for Tuning Quantum Devices and Nitrogen-Vacancy Imaging. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1662017.

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Asari, Vijayan, Paheding Sidike, Binu Nair, Saibabu Arigela, Varun Santhaseelan, and Chen Cui. PR-433-133700-R01 Pipeline Right-of-Way Automated Threat Detection by Advanced Image Analysis. Pipeline Research Council International, Inc. (PRCI), 2015. http://dx.doi.org/10.55274/r0010891.

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A novel algorithmic framework for the robust detection and classification of machinery threats and other potentially harmful objects intruding onto a pipeline right-of-way (ROW) is designed from three perspectives: visibility improvement, context-based segmentation, and object recognition/classification. In the first part of the framework, an adaptive image enhancement algorithm is utilized to improve the visibility of aerial imagery to aid in threat detection. In this technique, a nonlinear transfer function is developed to enhance the processing of aerial imagery with extremely non-uniform l

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Doerry, Armin Walter. Basics of Polar-Format algorithm for processing Synthetic Aperture Radar images. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1044949.

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