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SPIHT算法是压缩编码效率很高的静止图像压缩编码算法。针对原算法没有从最佳率失真的角度出发来选择初始量化门限这一不足之处 ,提出了一种改进的 SPIHT算法。通过理论计算和试验分析 ,得到初始量化门限 T0 和编码失真的关系 ,并导出搜索最优初始量化门限 T0 的简单迭代方法。改进的 SPIHT算法能根据输入图像的特性和给定的编码输出码率自适应地选择最优初始量化门限 T0 。在相同输出码率的条件下 ,改进的 SPIHT算法比原算法峰值信噪比提高最多达 0 .6 d B
The SPIHT algorithm is a still image compression algorithm with high compression efficiency. Aiming at the shortcomings that the original algorithm did not select the initial quantization threshold from the perspective of optimal rate distortion, an improved SPIHT algorithm was proposed. Through the theoretical calculation and experimental analysis, the relationship between the initial quantization threshold T0 and coding distortion is obtained, and a simple iterative method of searching for the optimal initial quantization threshold T0 is derived. The improved SPIHT algorithm can adaptively select the optimal initial quantization threshold T0 according to the characteristics of the input image and the given code output code rate. Under the condition of the same output bit rate, the improved SPIHT algorithm can improve the peak signal to noise ratio of the original algorithm up to 0.6 dB