Abstract
AbstractImage as an important information carrier, direct transmission and storage require high bandwidth and storage space, so proper compression is of great practical significance. Among many image compression algorithms, wavelet transform image compression can decompose the image with multi-level resolution, and can be progressive coding, which is very suitable for low bit rate image compression. Embedded Zerotree Wavelet (EZW) algorithm is an effective coding technique for low bit rate image compression, but it exits large redundancy. In this study, the authors improves the EZW algorithm and puts forward the IM-EZW algorithm. IM-EZW retain the characteristics of progressive, and increase the number of uncoded coefficients through new symbols, and use T compressors to reduce the number of bits. We use the peak-signal-noise ratio (PSNR) as the evaluation criteria and calculate it at the different compression rates. The experimental results show that IM-EZW has distinct advantages over the classical EZW and outperforms Set Partitioning in Hierarchical Trees (SPIHT).KeywordsEmbedded zerotree waveletImage compressionWavelet transform
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