Block Matching. Furht, B., editor In Encyclopedia of Multimedia, pages 55–56. Springer US, 2008. 00000
Block Matching [link]Paper  abstract   bibtex   
DefinitionBlock matching is the most widely used method for disparity estimation in stereo coding algorithms.Disparity/depth estimation is an important key step in many stereo coding algorithms, since it can be used to de-correlate information obtained from a stereo pair. In the predictive coding framework (consisting of disparity estimation/compensation, transform/quantization, and entropy coding), the redundancy is reduced by compensating the target image from the reference image with the disparity vectors.Block matching is the most widely used method for disparity estimation and is simple and effective to implement. The basic idea of block matching is to segment the target image into fixed size blocks and find for each block the corresponding block that provides the best match from the reference image. In general, the block minimizing the estimation error is usually selected as the matching block. However, block matching with a simple error measure may not yield smooth dis ...
@incollection{furht_block_2008,
	title = {Block {Matching}},
	copyright = {©2008 Springer-Verlag},
	isbn = {978-0-387-74724-8 978-0-387-78414-4},
	url = {http://link.springer.com/referenceworkentry/10.1007/978-0-387-78414-4_132},
	abstract = {DefinitionBlock matching is the most widely used method for disparity estimation in stereo coding algorithms.Disparity/depth estimation is an important key step in many stereo coding algorithms, since it can be used to de-correlate information obtained from a stereo pair. In the predictive coding framework (consisting of disparity estimation/compensation, transform/quantization, and entropy coding), the redundancy is reduced by compensating the target image from the reference image with the disparity vectors.Block matching is the most widely used method for disparity estimation and is simple and effective to implement. The basic idea of block matching is to segment the target image into fixed size blocks and find for each block the corresponding block that provides the best match from the reference image. In general, the block minimizing the estimation error is usually selected as the matching block. However, block matching with a simple error measure may not yield smooth dis ...},
	language = {en},
	urldate = {2016-05-03},
	booktitle = {Encyclopedia of {Multimedia}},
	publisher = {Springer US},
	editor = {Furht, Borko},
	year = {2008},
	note = {00000},
	pages = {55--56}
}
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