Topic
Sum of absolute differences
About: Sum of absolute differences is a research topic. Over the lifetime, 1004 publications have been published within this topic receiving 11385 citations.
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Patent•
27 Feb 1998
TL;DR: In this article, a system for coding of digital video images such as bi-directionally predicted video object planes (B-VOPs), in particular, where the B-VOPS and/or a reference image used to code the BVOP is interlaced coded, is presented.
Abstract: A system for coding of digital video images such as bi-directionally predicted video object planes (B-VOPs), in particular, where the B-VOP and/or a reference image used to code the B-VOP is interlaced coded. For a B-VOP macroblock which is co-sited with a field predicted macroblock of a future anchor picture, direct mode prediction is made by calculating four field motion vectors, then generating the prediction macroblock. The four field motion vectors and their reference fields are determined from (1) an offset term of the current macroblock's coding vector, (2) the two future anchor picture field motion vectors, (3) the reference field used by the two field motion vectors of the co-sited future anchor macroblock, and (4) the temporal spacing, in field periods, between the current B-VOP fields and the anchor fields. Additionally, a coding mode decision process for the current MB selects a forward, backward, or average field coding mode according to a minimum sum of absolute differences (SAD) error which is obtained over the top and bottom fields of the current MB.
226 citations
TL;DR: This correspondence shows the development of two-stage template matching with cross correlation as the similarity measure with significant speed-up over the one-stage process.
Abstract: Two-stage template matching with sum of absolute differences as the similarity measure has been developed by Vanderburg and Rosenfeld [1], [2]. This correspondence shows the development of two-stage template matching with cross correlation as the similarity measure. The threshold value of the first-stage is derived analytically and its validity is verified experimentally. Considerable speed-up over the one-stage process can be obtained by introducing only a small false dismissal probability.
212 citations
TL;DR: A Census-based stereo matching algorithm that handles difficult areas for stereo matching, such as areas with low texture, very well in comparison to state-of-the-art real-time methods and can successfully eliminate false positives to provide reliable 3D data.
206 citations
Patent•
28 Sep 1998
TL;DR: In this paper, a method for encoding an original image and decoding the encoded image to generate a representation of the original image is also disclosed, where the comparator and the decoder units determine the quantized colors for each encoded image block and map each pixel to one of the derived quantized colours.
Abstract: An image processing system (205) includes an image encoder system (220) and an image decoder system (230) that are coupled together. The image encoder system (220) includes an image decomposer (315) and a block encoder (318) that are coupled together. The block encoder (318) includes a color quantizer (335) and a bitmap construction module (340). The image decomposer (315) breaks an original image into blocks. Each block (260) is then processed by the block encoder (318a-nth). Specifically, the color quantizer (335) selects some number of base points, or codewords, that serve as reference pixel values, such as colors, from which quantized pixel values are derived. The bitmap construction module (340) then maps each pixel colors to one of the derived quantized colors. The codewords and bitmap are output as encoded image blocks (320). The decoder system (230) includes a block decoder (505a-mth). The block decoder (505a-mth) includes a block type detector (520), one or more decoder units, and an output selector (523). Using the codewords of the encoded data blocks, the comparator and the decoder units determine the quantized colors for the encoded image block and map each pixel to one of the quantized colors. The output selector (523) outputs the appropriate color, which is ordered in an image composer with the other decoded blocks to output an image representative of the original image. A method for encoding an original image and for decoding the encoded image to generate a representation of the original image is also disclosed.
163 citations
TL;DR: A new one-dimensional (1-D) very large-scale integration architecture for full-search VBSME (FSVBSME), which can process up to 41 MV sub-blocks (within a macroblock) in the same number of clock cycles.
Abstract: With the advent of new video standards such as MPEG-4 part-10 and H.264/H.26L, demands for advanced video coding, particularly in the area of variable block size video motion estimation (VBSME), are increasing. In this paper, we propose a new one-dimensional (1-D) very large-scale integration architecture for full-search VBSME (FSVBSME). The VBS sum of absolute differences (SAD) computation is performed by re-using the results of smaller sub-block computations. These are distributed and combined by incorporating a shuffling mechanism within each processing element. Whereas a conventional 1-D architecture can process only one motion vector (MV), this new architecture can process up to 41 MV sub-blocks (within a macroblock) in the same number of clock cycles.
162 citations