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Secure Transmission of Compressed Medical Image Sequences on Communication Networks Using Motion Vector Watermarking
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作者 Rafi Ullah Mohd Hilmi bin Hasan +1 位作者 Sultan Daud Khan Mussadiq Abdul Rahim 《Computers, Materials & Continua》 SCIE EI 2024年第3期3283-3301,共19页
Medical imaging plays a key role within modern hospital management systems for diagnostic purposes.Compression methodologies are extensively employed to mitigate storage demands and enhance transmission speed,all whil... Medical imaging plays a key role within modern hospital management systems for diagnostic purposes.Compression methodologies are extensively employed to mitigate storage demands and enhance transmission speed,all while upholding image quality.Moreover,an increasing number of hospitals are embracing cloud computing for patient data storage,necessitating meticulous scrutiny of server security and privacy protocols.Nevertheless,considering the widespread availability of multimedia tools,the preservation of digital data integrity surpasses the significance of compression alone.In response to this concern,we propose a secure storage and transmission solution for compressed medical image sequences,such as ultrasound images,utilizing a motion vector watermarking scheme.The watermark is generated employing an error-correcting code known as Bose-Chaudhuri-Hocquenghem(BCH)and is subsequently embedded into the compressed sequence via block-based motion vectors.In the process of watermark embedding,motion vectors are selected based on their magnitude and phase angle.When embedding watermarks,no specific spatial area,such as a region of interest(ROI),is used in the images.The embedding of watermark bits is dependent on motion vectors.Although reversible watermarking allows the restoration of the original image sequences,we use the irreversible watermarking method.The reason for this is that the use of reversible watermarks may impede the claims of ownership and legal rights.The restoration of original data or images may call into question ownership or other legal claims.The peak signal-to-noise ratio(PSNR)and structural similarity index(SSIM)serve as metrics for evaluating the watermarked image quality.Across all images,the PSNR value exceeds 46 dB,and the SSIM value exceeds 0.92.Experimental results substantiate the efficacy of the proposed technique in preserving data integrity. 展开更多
关键词 Block matching algorithm(BMA) compression full-search algorithm motion vectors ultrasound image sequence WATERMARKING
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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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