Fast slant transform with sequency increment and its application in image compression
| Autor: | Hong Chen, Zheng-Xin Hou, Xue-Lei Li, Ni-Ni Xu |
|---|---|
| Rok vydání: | 2005 |
| Předmět: |
Move-to-front transform
Transform theory business.industry Top-hat transform Discrete Fourier transform Computer Science::Computer Vision and Pattern Recognition Discrete cosine transform Computer vision Artificial intelligence business Transform coding Data compression Mathematics Image compression |
| Zdroj: | Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826). |
| DOI: | 10.1109/icmlc.2004.1384555 |
| Popis: | This work analyses the rule of the base vector arrangement for slant transform, gives the equations and the fast algorithms for the slant transform of arbitrary order 2" with base vectors arranged in sequency increment, makes traditional slant transform theory more consummate. Using this algorithm in image compression, the data entropy in the transform domain approaches that of the commonly used DCT, but the operation speed is faster. This algorithm is suitable for the orthogonal transformation where high speed and hardware implementation are required. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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