Aiming at the shortcomings of the original SPIHT algorithm, such as repeated scanning and failure to fully consider the visual characteristics of the human eye (HVS), the original algorithm was improved by introducing the visual characteristics of the human eye, DPCM coding and establishing the maximum value table. The simulation results show that the improved algorithm has improved the subjective effect of the reconstructed image, the peak signal-to-noise ratio and the coding and decoding efficiency compared with the original algorithm. Keywords: wavelet transform; SPIHT; image compression The set splitting tree (SPIHT) still image compression coding algorithm based on wavelet transform proposed by Said and Pearlman is considered to be one of the most advanced methods at present. The algorithm adopts an effective spatial direction tree and bit plane coding method, which can not only obtain high compression coding efficiency, but also generate a code stream that supports multiple bit rates. However, the transformation process in the algorithm is complex, there are repeated scans and the visual characteristics of the human eye are not fully considered. Aiming at the above shortcomings, the original algorithm is improved in this paper, which improves the coding and decoding efficiency, the subjective effect of the reconstructed image and the peak signal-to-noise ratio.
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