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Hardware Architecture Design of Block-Matching and 3D-Filtering Denoising Algorithm
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作者 张昊 刘文江 +2 位作者 王若琳 刘涛 戎蒙恬 《Journal of Shanghai Jiaotong university(Science)》 EI 2016年第2期173-183,共11页
Block-matching and 3D-filtering(BM3D) is a state of the art denoising algorithm for image/video,which takes full advantages of the spatial correlation and the temporal correlation of the video. The algorithm performan... Block-matching and 3D-filtering(BM3D) is a state of the art denoising algorithm for image/video,which takes full advantages of the spatial correlation and the temporal correlation of the video. The algorithm performance comes at the price of more similar blocks finding and filtering which bring high computation and memory access. Area, memory bandwidth and computation are the major bottlenecks to design a feasible architecture because of large frame size and search range. In this paper, we introduce a novel structure to increase data reuse rate and reduce the internal static-random-access-memory(SRAM) memory. Our target is to design a phase alternating line(PAL) or real-time processing chip of BM3 D. We propose an application specific integrated circuit(ASIC) architecture of BM3 D for a 720 × 576 BT656 PAL format. The feature of the chip is with 100 MHz system frequency and a 166-MHz 32-bit double data rate(DDR). When noise is σ = 25, we successfully realize real-time denoising and achieve about 10 d B peak signal to noise ratio(PSNR) advance just by one iteration of the BM3 D algorithm. 展开更多
关键词 block-matching and 3D-filtering(BM3D) denoising algorithm IMPLEMENTATION BLOCK-MATCHING 3D-filtering AGGREGATION
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Numerical Comparisons of Different Imaging Algorithms
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作者 Soulef Bougueroua Nourreddine Daili 《Journal of Applied Mathematics and Physics》 2023年第9期2671-2690,共20页
Image processing is the set of operations performed to extract “information” from the image. An interesting problem in digital image processing is the restoration of degraded images. It often happens that the result... Image processing is the set of operations performed to extract “information” from the image. An interesting problem in digital image processing is the restoration of degraded images. It often happens that the resulting image is different from the expected image. Our problem will therefore be to recover an image close to the original image from a poor quality image (that has been skewed by Gaussian and additive noise). There are several algorithms on how we can improve the broken image in better quality. We present in this paper our numerical results obtained with the models of Tikhonov regularization, ROF, Vese Osher, anisotropic and isotropic TV denoising algorithms. 展开更多
关键词 COMPARATIVE denoising algorithms Image Restoration
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