Empirical evaluation of EZW and other encoding techniques in the wavelet-based image compression domain

Abstract

This paper discusses about embedded zerotree wavelet (EZW) and other wavelet-based encoding techniques employed in lossy image compression. The objective of this paper is two fold. Primarily wavelet-based encoding techniques such as EZW, set partitioning in hierarchical trees (SPIHT), wavelet difference reduction (WDR), adaptively scanned wavelet difference reduction (ASWDR), set partitioned embedded block (SPECK), compression with reversible embedded wavelet (CREW) and space frequency quantization (SFQ) are implemented and their performance is analyzed. Second, wavelet-based compression schemes such as Haar, Daubechies and Biorthogonal are used to evaluate the performance of encoding techniques. The performance parameters such as peak signal-to-noise ratio (PSNR) and mean square error (MSE) are used for evaluation purpose. From the results it is observed that the performance of SPIHT encoding technique is providing better results when compared to other encoding schemes.