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3D Filtering by block matching and Convolutional Neural Network for Image Denoising

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Journal of Computer Science & Technology 2018年第4期33卷 838-848页

作者： Bei-Ji Zou Yun-Di Guo Qi He Ping-Bo Ouyang Ke Liu Zai-Liang Chen School of Information Science and Engineering Central South University Changsha 410083 China Center for Information and Automation of China Nonferrous Metals Industry Association Changsha 410011 China Center for Ophthalmic Imaging Research Central South University Changsha 410083 China

block matching based 3D filtering methods have achieved great success in image denoising tasks. However the manually set filtering operation could not well describe a good model to transform noisy images to clean images. In this paper, we introduce convolutional neural network （CNN） for the 3D filtering step to learn a well fitted model for denoising. With a trainable model, prior knowledge is utilized for better mapping from noisy images to clean images. This block matching and CNN joint model （BMCNN） could denoise images with different sizes and different noise intensity well, especially images with high noise levels. The experimental results demonstrate that among all competing methods, this method achieves the highest peak signal to noise ratio （PSNR） when denoising images with high noise levels （σ 〉 40）, and the best visual quality when denoising images with all the tested noise levels.

关键词： block matching convolutional neural network (CNN) denoising 3D filtering

Multi-focus image fusion based on block matching in 3D transform domain

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Journal of Systems Engineering and Electronics 2018年第2期29卷 415-428页

作者： YANG Dongsheng HU Shaohai LIU Shuaiqi MA Xiaole SUN Yuchao Institute of Information Science Beijing Jiaotong UniversityBeijing 100044China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing 100044China College of Electronic and Information Engineering Hebei UniversityBaoding 071002China The Third Research Institute China Electronics Technology Group CorporationBeijing 100015China

Fusion methods based on multi-scale transforms have become the mainstream of the pixel-level image fusion. However,most of these methods cannot fully exploit spatial domain information of source images, which lead to the degradation of *** paper presents a fusion framework based on block-matching and 3D(BM3D) multi-scale transform. The algorithm first divides the image into different blocks and groups these 2D image blocks into 3D arrays by their similarity. Then it uses a 3D transform which consists of a 2D multi-scale and a 1D transform to transfer the arrays into transform coefficients, and then the obtained low-and high-coefficients are fused by different fusion rules. The final fused image is obtained from a series of fused 3D image block groups after the inverse transform by using an aggregation process. In the experimental part, we comparatively analyze some existing algorithms and the using of different transforms, e.g. non-subsampled Contourlet transform(NSCT), non-subsampled Shearlet transform(NSST), in the 3D transform step. Experimental results show that the proposed fusion framework can not only improve subjective visual effect, but also obtain better objective evaluation criteria than state-of-the-art methods.

关键词： image fusion block matching 3D transform block-matching and 3D(BM3D) non-subsampled Shearlet transform(NSST)

A Simple and Efficient Algorithm for block matching Motion Estimation in Video Coding

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A Simple and Efficient Algorithm for Block Matching Motion E...

A Fast block—matching Algorithm Using Smooth Motion Vector Field Adaptive Search Technique

1998 International Conference on Communication Technology

作者： Jia Zhike Cui Huijuan Tangkun Feng Chongxi Tsinghua Univeristy

ISBN: (纸本)7800908275

＜正＞Computational complexity and accuracy of motion vector are two key factors of block matching motion estimation in video *** paper proposes a simple and efficient algorithm named Edge Pixels Classification（EPC） *** to the fact that human eyes are highly sensitive to the motion of edge,the EPC algorithm makes full use of the pixels in edge. After edge detection,the pixels in edge are classified into two categories:matching pixels and mismatching *** best matching block within a search area is the one with the highest number of matching *** with some well-known algorithms which use mean absolute difference（MAD） matching criterion,the EPC algorithm can provide much higher performance with much lower computational complexity.

关键词： Video coding Motion estimation block matching Edge detection

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Journal of Computer Science & Technology 2003年第1期18卷 14-21页

作者：李波李炜涂亚明 Digital Media Laboratory Department of Computer Science and Engineering Beijing University of Aeronautics and Astronautics Beijing 100083 P.R. China

In many video standards based on inter-frame compression such as H.26x and MPEG, block-matching algorithm has been widely adopted as the method for motion estimation because of its simplicity and effectiveness. Nevertheless, since motion estimation is very complex in computing. Fast algorithm for motion estimation has always been an important and attractive topic in video compression. From the viewpoint of making motion vector field smoother, this paper proposes a new algorithm SMVFAST. On the basis of motion correlation, it predicts the starting point by neighboring motion vectors according to their SADs. Adaptive search modes are usedin its search process through simply classifying motion activity. After discovering the ubiquitous ratio between the SADs of the collocated blocks in the consecutive frames, the paper proposes an effective half-stop criterion that can quickly stop the search process with good enough *** show that SMVFAST obtains almost the same results as the full search at very low computation cost, and outperforms MVFAST and PMVFAST in speed and quality, which are adopted by MPEG-4.

关键词： video encoder video compression motion estimation block matching MPEG H.263

H.264 MOTION ESTIMATION ALGORITHM BASED ON VIDEO SEQUENCES ACTIVITY

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Journal of Electronics(China) 2008年第1期25卷 125-128页

作者： Hu Weiwei Zhang Qishan School of Electronic and Information Engineering Beijing University of Aeronautics and Astronautics Beijing 100083 China

Motion estimation is an important part of H.264/AVC encoding progress, with high com- putational complexity. Therefore, it is quite necessary to find a fast motion estimation algorithm for real-time applications. The algorithm proposed in this letter adjudges the macroblocks activity degree first; then classifies different video sequences, and applies different search strategies according to the result. Experiments show that this method obtains almost the same video quality with the Full Search (FS) algorithm but with reduced more than 95% computation cost.

关键词： Motion estimation block matching Diamond search H.264

Automatic detection and removal of static shadows

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Journal of Measurement Science and Instrumentation 2020年第4期11卷 343-350页

作者： HOU Tao WU Hai-ping School of Automation and Electrical Engineering Lanzhou Jiaotong UniversityLanzhou 730070China

In case of complex textures,existing static shadow detection and removal algorithms are prone to false detection of the *** solve this problem,a static shadow detection and removal algorithm based on support vector machine(SVM)and region sub-block matching is ***,the original image is segmented into several superpixels,and these superpixels are clustered using mean-shift clustering algorithm in the superpixel ***,these features such as color,texture,brightness,intensity and similarity of each area are *** features are used as input of SVM to obtain shadow binary images through training in non-operational ***,soft matting is used to smooth the boundary of shadow binary ***,after finding the best matching sub-block for shadow sub-block in the illumination region based on regional covariance feature and spatial distance,the shadow weighted average factor is introduced to partially correct the sub-block,and the light recovery operator is used to partially light the *** experimental results show the number of false detection of the pixels is *** addition,it can remove shadows effectively for the image with rich textures and uneven shadows and make a natural transition at the boundary between shadow and light.

关键词： shadow detection shadow removal feature extraction support vector machine(SVM) block matching light recovery operator

A Two-Stage Algorithm of High Resolution Image Alignment for Mobile Applications

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Journal of Computer and Communications 2016年第4期4卷 36-51页

作者： Ren-You Huang Lan-Rong Dung Tang-Suan Hong Institute of Electrical Control Engineering National Chiao Tung University Taiwan Department of Electrical and Computer Engineering National Chiao Tung University Taiwan Institute of Communications Engineering National Chiao Tung University Taiwan

Global motion estimation (GME) algorithms are widely applied to computer vision and video processing. In the previous works, the image resolutions are usually low for the real-time requirement (e.g. video stabilization). However, in some mobile devices applications (e.g. image sequence panoramic stitching), the high resolution is necessary to obtain satisfactory quality of panoramic image. However, the computational cost will become too expensive to be suitable for the low power consumption requirement of mobile device. The full search algorithm can obtain the global minimum with extremely computational cost, while the typical fast algorithms may suffer from the local minimum problem. This paper proposed a fast algorithm to deal with 2560 × 1920 high-resolution (HR) image sequences. The proposed method estimates the motion vector by a two-level coarse-to-fine scheme which only exploits sparse reference blocks (25 blocks in this paper) in each level to determine the global motion vector, thus the computational costs are significantly decreased. In order to increase the effective search range and robustness, the predictive motion vector (PMV) technique is used in this work. By the comparisons of computational complexity, the proposed algorithm costs less addition operations than the typical Three-Step Search algorithm (TSS) for estimating the global motion of the HR images without the local minimum problem. The quantitative evaluations show that our method is comparable to the full search algorithm (FSA) which is considered to be the golden baseline.

关键词： Global Motion Estimation block matching High Resolution Image Alignment Mobile Applications

block-Based Image Processing:Digital Speckle Correlation and Windowed Fourier Transform

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Block-Based Image Processing:Digital Speckle Correlation and...

A Novel Approach to Fast Motion Vector Search

International Conference on Experimental Mechanics 2008 (ICEM 2008)

作者： Hock Soon Seah Anand Asundi FSchool of Computer Engineering Nanyang Technolgocial UniversitySingapore School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore

＜正＞Optical techniques are often used for accurate and non-contact ***-dimensional images are often recorded as intermediate results for further *** speckle correlation and fringe pattern analysis are typical exampl... 详细信息

关键词： block matching digital speckle correlation windowed Fourier transform

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A Novel Approach to Fast Motion Vector Search