EZW AND SPIHT IMAGE COMPRESSION TECHNIQUES FOR HIGH RESOLUTION SATELLITE IMAGERIES
K. Nagamani · 2011
Image compression methods employing wavelet transforms have been successfully implemented to provide high compression rates while maintaining good image quality. The significance map is a binary decision indicates if a coefficient of a 2-D discrete wavelet transform (DWT) has a zero or nonzero quantized value. The coding of the significance map, or in other words, the positions of those coefficients that will be transmitted as nonzero values is one of the important aspects of low bit rate image coding. This results in a considerable improvement in encoding the significance map, and hence, a higher efficiency in compression. Applying the DWT coefficients and using EZW (Embedded Zero tree wavelet) and SPIHT (Set Partitioning in Hierarchical Trees) coding techniques the compression ratios and PSNR are determined for a standard LENA Image and high resolution Satellite urban image (SatImg) . The results obtained for EZW coding are compared with that of SPIHT coding for the same set of images. The results show that it is possible to achieve higher compression ratios ~8 and PSNR ~29.20 for SPIHT coding compared to EZW coding where the compression ratio ~1.07, PSNR ~13.07 can be achievable for applications relating to satellite urban imageries. Both the techniques indicate that maximum compression ratios are achievable for standard Lena Image for an acceptable quality of the image. The results are presented and discussed in the paper.