Abstract
Because the perceptual compressive sensing framework can achieve a much better performance than the legacy compressive sensing framework, it is very promising for the compressive sensing based image compression system. In this paper, we propose an innovative adaptive perceptual block compressive sensing scheme. Firstly, a new block-based statistical metric which can more appropriately measure each block's sparsity and perceptual sensibility is devised. Then, the approximated theoretical minimum measurement number for each block is derived from the new block-based metric and used as weight for adaptive measurements allocation. The obtained experimental results show that our scheme can significantly enhance both objective and subjective performance of a perceptual compressive sensing framework.
Original language | English |
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Pages (from-to) | 1702-1706 |
Number of pages | 5 |
Journal | IEICE Transactions on Information and Systems |
Volume | E99D |
Issue number | 6 |
DOIs | |
Publication status | Published - Jun 2016 |
Keywords
- Adaptive Measurements Allocation
- Discrete Cosine Transform
- Image Compression
- Perceptual Compressive Sensing