In this paper, an adaptive genetic block-matching algorithm is proposed for video compression. Specially, some novel adaptive elements, including initialization, parent selection and termination rule, are contrived. E...
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ISBN:
(纸本)0819441880
In this paper, an adaptive genetic block-matching algorithm is proposed for video compression. Specially, some novel adaptive elements, including initialization, parent selection and termination rule, are contrived. Extensive simulations with different test video sequences have confirmed that the proposed algorithm can improve the preciseness of block-matching search, while keeping low computational complexity.
In this letter, the impact of a regularization of motion vectors (MVs) on the performance of a block-DCT based video coder (H.263) is addressed. Postprocessing is accomplished by exploiting both the spatial correlatio...
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In this letter, the impact of a regularization of motion vectors (MVs) on the performance of a block-DCT based video coder (H.263) is addressed. Postprocessing is accomplished by exploiting both the spatial correlation of the vector field and the confidence of the estimated block vectors, A recently proposed adaptive scheme for MV smoothing, based on the theory of vector median Filters, is adjusted and embedded into an H.263 coder. With a bit stream that is perfectly H.263-compatible, results are improved, especially for very low bit rates and complex motion of the scene.
A full-search based block-matching algorithm for motion estimation has a major problem of significant computational load, To solve this problem, extensive research in fast-motion estimation algorithms have been carrie...
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A full-search based block-matching algorithm for motion estimation has a major problem of significant computational load, To solve this problem, extensive research in fast-motion estimation algorithms have been carried out, However, most of them have some degradation in the predicted image from the reduced computation, To decrease the amount of significant computation of the full-search algorithm, we propose a fast block-matching algorithm based on an adaptive matching scan and representative pixels without any degradation of the predicted image. By using Taylor series expansion, we obtain the representative pixels and show that the block-matching errors from the reference block and candidate blocks are proportional to the block complexity, With the derived result, we propose a fast full-search algorithm with adaptive scan direction in blockmatching. Experimentally, our proposed algorithm is very efficient in terms of computational speedup, and is the fastest among all the conventional full-search algorithms, Therefore, our algorithm is useful in VLSI implementation of video encoders for real-time encoding.
A fast block-matching algorithm for motion estimation is described for interframe image coding. Utilizing the fact that the motion is searched by a macroblock basis while the compression is performed by a block basis ...
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A fast block-matching algorithm for motion estimation is described for interframe image coding. Utilizing the fact that the motion is searched by a macroblock basis while the compression is performed by a block basis in many video compression standards, the proposed algorithm produces high PSNR and fast computation while keeping the bit-rate as low as those of conventional fast algorithms. The proposed algorithm uses the subblock sum as a matching parameter and the reversed square sum as a matching criterion. The new matching parameter and criterion reduce the total number of computations for blockmatching and also keep the quality of the decompressed image. The computational complexity and the compression performance of the proposed algorithm are compared with those of other block-matching algorithms. (C) 1999 Elsevier Science B.V. All rights reserved.
In this paper, a high-throughput modular architecture for a logarithmic search block-matching algorithm is presented. The design efforts are focused on exploiting the search area data dependencies using special data i...
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In this paper, a high-throughput modular architecture for a logarithmic search block-matching algorithm is presented. The design efforts are focused on exploiting the search area data dependencies using special data input ordering constraints. The input bandwidth problem has been solved by a random access on-chip memory, and a simple address generation procedure has been described. Furthermore, this architecture can handle a large search range with unequal horizontal and vertical spans using a technique called pipeline intel leaving. Compared to the existing architectures for the three-step search BMA, this architecture delivers a high throughput rate with fewer input lines, and is linearly scalable.
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