Imaging and video compression using embedded zerotree coding

• Main Author: Yin, Che-Yi
• Language: ENG
• Published: ScholarWorks@UMass Amherst 2000
• Subjects: Electrical engineering|Computer science
• Online Access: https://scholarworks.umass.edu/dissertations/AAI9960806

In this dissertation, we investigate several embedded zerotree wavelet (EZW) coding techniques for designing image and video coders. Four topics addressed include: (1) EZW coding using non-uniform quantization, (2) Adaptive EZW coding using rate-distortion criterion, (3) Modified “set partitioning in hierarchical trees” (SPIHT) and (4) Video coding using segmentation, regional wavelet packet, and adaptive EZW. The first three topics are applications for image compression, and the last topic is an application for video compression. The embedded zerotree wavelet image compression algorithm developed by Shapiro is the most popular wavelet-based image coder to date. First, we aim to modify the quantization characteristics of EZW by the following two approaches: (1) Non-uniform quantizer: we design two non-uniform quantization schemes, nonuniform EZW and Lloyd-Max EZW. (2) Rate-distortion criterion: we develop adaptive EZW, where we introduce adaptive step sizes for each subband. The best set of step sizes is found by using Lagrangian optimization, where two coding environments, independent and dependent, are considered. The proposed image coder retains all the good features of EZW, namely, embedded coding, progressive transmission, order of importance. Experimental results show that the proposed image coders perform significantly better than the standard EZW algorithm. Then, we aim at the significance map coding of EZW by designing a new set partition algorithm. We adopt and modify the framework of the SPIHT. The new set partition algorithm can catch more insignificant coefficients than the original algorithm. The experimental results show that the proposed algorithms achieve significant improvement over the standard EZW and SPIHT algorithms. Finally, we present a new video coding algorithm. This algorithm can effectively exploit the temporal, spatial and frequency information within a video sequence through a combination of segmentation, regional wavelet packet, adaptive EZW, and DPCM techniques. The proposed video coder provides notable improvement in R-D characteristics over similar algorithms.