Block matching algorithms (BMAs) are widely used in motion analyses of 2D image data. Comparisons are made between one subregion and all adjacent subregions at consecutive timesteps to seek the the most likely 2D evolution of the subregion using the minimisation of various cost functions such as crosscorrelation coefficient, sum of the absolute value of difference and sum of squared difference.The most commonly used ME technique in video coding is the block matching algorithm, mainly due to its simplicity and good performance[2. Block matching assists to choose a motion vector for each macro block instead of using a motion vector for each pixel, and block-matching algorithm
Dec 16, 2011 Block Matching Algorithms for Motion Estimation. The algorithms that are evaluated in this paper are widely accepted by the video compressing community and have been used in implementing various standards, ranging from MPEG1 H. 261 to MPEG4 H. 263. The paper also presents a very brief introduction to the entire flow of video compression.
Blockmatching algorithm. A Block Matching Algorithm is a way of locating matching macroblocks in a sequence of digital video frames for the purposes of motion estimation. The underlying supposition behind motion estimation is that the patterns corresponding to objects and background in a frame of video sequence move within the frame to form corresponding objects on the subsequent frame. This grouping technique is called blockmatching, it is typically used to group similar groups across different frames of a digital video, BM3D on the other hand may group macroblocks within a single frame. All image fragments in a group are then stacked together to form 3D cylinderlike shapes.block-matching algorithm Blockmatching algorithm Motivation. Motion estimation is the process of determining motion vectors that describe Evaluation Metrics. A metric for matching a macroblock with another block is based on a cost function. Algorithms. Block Matching algorithms have been researched since mid1980's.