In this paper, we propose a new lossless MRME algorithm applicable to the current international video coding standards in which we remove only unnecessary computation in calculating block-matching error without any degradation of prediction quality. Our proposed algorithm employs the MRME scheme, the PDE (Partial Distortion Elimination), the spiral search, and the adaptive matching scan from the image complexity of the reference block. Important thing in the PDE algorithm is that how fast impossible candidates are detected by removing unnecessary computation. In this paper, we use the fact that the block-matching error is proportional to the complexity of the reference block with Taylor series expansion. The motivation of the proposing algorithm is using image complexity to find the impossible candidates faster. Local complexity of subblock is defined as spatial complexity of image data for each subblock and measured with gradient magnitude. From the experimental results, our proposed algorithm saves 50%~80% compared with the computations of the original MRME algorithm, while our proposed algorithm has the same prediction quality as that of the original MRME algorithm. Our proposed algorithm is applicable to the MPEG video codec such as MPEG-2 and MPEG-4 AVC and will be useful to real-time video coding applications.
To accelerate decoding fractal-coded images, researchers have actively investigated methods for deriving dependency regions. This paper describes a novel approach to expanding dependency regions for fast fractal image decoding. Our approach carefully identifies and encodes data dependency at encoding time in such a way that the decoder guarantees to get the dependency regions and further expands the dependency regions effectively. The experimental results show our approach improves the efficiency of the fractal decoding process significantly.
This paper describes novel fractal coding scheme that significantly improves the efficiency of the fractal image decoding. Removing great number of contractive transforms required by the decoding process can significantly reduce the decoding time. The proposed decoding scheme effectively finds dependency regions, whose range blocks are decoded by only one contractive transformation, from an encoded image. The experimental results show the significance of our proposed scheme in improving the efficiency of the fractal decoding process.
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