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
This paper proposes an electronic image stabilization algorithm based on efficient block matching on the plane. This algorithm uses a hexagonal search algorithm, and uses the bit-planes to estimate and compensate for ...This paper proposes an electronic image stabilization algorithm based on efficient block matching on the plane. This algorithm uses a hexagonal search algorithm, and uses the bit-planes to estimate and compensate for the translational motion between video sequences at the same time;As for the rotary motion vector generated in the video sequences, in order to highlight the intensity change of the image sequence, the algorithm firstly conducts Laplace transform for the reference frame, then select a number of characteristics at the image edge to make block matching with the current frame, calculate and compensate for the rotational movement that may exist finally. Through theoretical analysis and simula-tion, we prove that, as for a mixed translational and rotational motion video sequences, the proposed algorithm can reduce required time for block matching computation ,while improving the accuracy of the electronic image stabilization.展开更多
为改善传统算法对量块特征匹配计算大、精度不足的问题,提出一种基于SURF(speed up robust feature)改进的算法。该算法对采集到的图像预处理得到有效匹配区域,筛除无关特征点的干扰;判断矩阵的迹进一步剔除无效点;在欧式距离的基础上...为改善传统算法对量块特征匹配计算大、精度不足的问题,提出一种基于SURF(speed up robust feature)改进的算法。该算法对采集到的图像预处理得到有效匹配区域,筛除无关特征点的干扰;判断矩阵的迹进一步剔除无效点;在欧式距离的基础上得到模型筛选阈值,并运用随机抽样一致(RANSAC)算法进一步提纯匹配。通过实验分析比较,与传统算法相比,改进后算法正确率较高,具有较强鲁棒性。展开更多
基金the National Natural Science Foundation of China(No.61234001)
文摘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.
文摘This paper proposes an electronic image stabilization algorithm based on efficient block matching on the plane. This algorithm uses a hexagonal search algorithm, and uses the bit-planes to estimate and compensate for the translational motion between video sequences at the same time;As for the rotary motion vector generated in the video sequences, in order to highlight the intensity change of the image sequence, the algorithm firstly conducts Laplace transform for the reference frame, then select a number of characteristics at the image edge to make block matching with the current frame, calculate and compensate for the rotational movement that may exist finally. Through theoretical analysis and simula-tion, we prove that, as for a mixed translational and rotational motion video sequences, the proposed algorithm can reduce required time for block matching computation ,while improving the accuracy of the electronic image stabilization.
文摘为改善传统算法对量块特征匹配计算大、精度不足的问题,提出一种基于SURF(speed up robust feature)改进的算法。该算法对采集到的图像预处理得到有效匹配区域,筛除无关特征点的干扰;判断矩阵的迹进一步剔除无效点;在欧式距离的基础上得到模型筛选阈值,并运用随机抽样一致(RANSAC)算法进一步提纯匹配。通过实验分析比较,与传统算法相比,改进后算法正确率较高,具有较强鲁棒性。
