New image compression algorithm based on improved reversible biorthogonal integer wavelet transform

Libao Zhang; Xianchuan Yu

doi:10.1117/12.929169

15 October 2012 New image compression algorithm based on improved reversible biorthogonal integer wavelet transform

Libao Zhang, Xianchuan Yu

Proceedings Volume 8499, Applications of Digital Image Processing XXXV; 84990B (2012) https://doi.org/10.1117/12.929169
Event: SPIE Optical Engineering + Applications, 2012, San Diego, California, United States

Abstract

The low computational complexity and high coding efficiency are the most significant requirements for image compression and transmission. Reversible biorthogonal integer wavelet transform (RB-IWT) supports the low computational complexity by lifting scheme (LS) and allows both lossy and lossless decoding using a single bitstream. However, RB-IWT degrades the performances and peak signal noise ratio (PSNR) of the image coding for image compression. In this paper, a new IWT-based compression scheme based on optimal RB-IWT and improved SPECK is presented. In this new algorithm, the scaling parameter of each subband is chosen for optimizing the transform coefficient. During coding, all image coefficients are encoding using simple, efficient quadtree partitioning method. This scheme is similar to the SPECK, but the new method uses a single quadtree partitioning instead of set partitioning and octave band partitioning of original SPECK, which reduces the coding complexity. Experiment results show that the new algorithm not only obtains low computational complexity, but also provides the peak signal-noise ratio (PSNR) performance of lossy coding to be comparable to the SPIHT algorithm using RB-IWT filters, and better than the SPECK algorithm. Additionally, the new algorithm supports both efficiently lossy and lossless compression using a single bitstream. This presented algorithm is valuable for future remote sensing image compression.

Citation Download Citation

Libao Zhang and Xianchuan Yu "New image compression algorithm based on improved reversible biorthogonal integer wavelet transform", Proc. SPIE 8499, Applications of Digital Image Processing XXXV, 84990B (15 October 2012); https://doi.org/10.1117/12.929169

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KEYWORDS

Image compression

Wavelet transforms

Remote sensing

Discrete wavelet transforms

Computer programming

Algorithms

Wavelets

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