Optimization of LIS and LIP Encoding for SPIHT-Based Image Compression
Heting Nie, Xianwei Rong, Xiaoyan Yu · 2017
This paper presents an optimization scheme for encoding the list of insignificant sets (LIS) and the list of insignificant pixels (LIP) to reduce the redundancies existing in the conventional set partitioning in hierarchical trees (SPIHT) based image compression algorithm. This scheme is based upon the investigation of distribution characteristics of wavelet coefficients. A judgment method with a predetermined threshold value is used for the sorting pass of LIS to identify significant coefficients ahead of encoding the LIS. Assuming that all the coefficients in LIS are less than the threshold value, and then they will not be scanned and encoded by the SPIHT. Moreover, a flag representing the number of significant coefficients encoded was introduced for encoding LIP in order to stop scanning LIP once all the significant coefficients have been encoded. Experimental results with various benchmark images show that the modified SPIHT (MSPIHT) achieves better visual quality and higher Peak Signal to Noise Ratio (PSNR) gains. Furthermore, the number of output 0 bits is significantly decreased at various bit rates compared with the original SPIHT.