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A Lossless Image Compression Using Traditional and Lifting Based Wavelets

Author(s): B Eswara Reddy | K Venkata Narayana

Journal: Signal & Image Processing
ISSN 2229-3922

Volume: 3;
Issue: 2;
Start page: 213;
Date: 2012;
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Keywords: Wavelet | Image Compression | SPIHT | Lifting | Hand-designed

In this paper an attempt has been made to analyse different wavelet techniques for image compression.Both hand-designed and lifting based wavelets are considered. Hand designed wavelets considered in thiswork are Haar wavelet, Daubechie wavelet, Biorthognal wavelet, Demeyer wavelet, Coiflet wavelet andSymlet wavelet. Lifting based wavelet transforms considered are 5/3 and 9/7. Wide range of images,including both color and gray scale images were considered. These wavelet transforms are used tocompress the test images competitively by using Set Partitioning In Hierarchical Trees (SPIHT) algorithmand by incorporating lifting concepts. Set Partitioning In Hierarchical Trees is a new advanced algorithmbased on wavelet transform which is gaining attention due to many potential commercial applications inthe area of image compression. These algorithms resulted in practical advantages, such as, superior lowbit rate performance, bit-level compression, progressive transmission by pixel, accuracy and resolution.The SPIHT coder is also a highly refined version of the EZW algorithm and is a powerful imagecompression algorithm, that produces an embedded bit stream form, in which the best reconstructedimages shows a significant perceptual improvement as well as an increased PSNR.
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