Adaptive Split-and-Merge for Image Analysis and Coding
Riccardo Leonardi,Murat Kunt +1 more
- Vol. 0594, pp 2-9
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TLDR
In this paper, an approximation algorithm for two-dimensional (2-D) signals, e.g. images, is presented by partitioning the original signal into adjacent regions with each region being approximated in the least square sense by a 2-D analytical function.Abstract:
An approximation algorithm for two-dimensional (2-D) signals, e.g. images, is presented. This approximation is obtained by partitioning the original signal into adjacent regions with each region being approximated in the least square sense by a 2-D analytical function. The segmentation procedure is controlled iteratively to insure at each step the best possible quality between the original image and the segmented one. The segmentation is based on two successive steps: splitting the original picture into adjacent squares of different size, then merging them in an optimal way into the final region configuration. Some results are presented when the approximation is performed by polynomial functions.read more
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Image compression using binary space partitioning trees
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Space-Frequency Quantization for Image Compression With Directionlets
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Rate-Distortion Optimized Tree-Structured Compression Algorithms for Piecewise
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References
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