An improved wavelet image lossless compression algorithm

The wavelet transform divides image into different but interrelated multi-resolution and multi-level sub-bands, so quantization coding strategy of image wavelet coefficient has great flexibility. To address to energy aggregation and correlated features of image wavelet coefficient, Hilbert and singular value truncating were introduced to wavelet to propose an Improved Wavelet Lossless Compression Algorithm (IWLCA). It mainly performs classification rearrangement on low-frequency sub-band coefficient of wavelet image in accordance with Hilbert curve, but conducts singular value truncating transform on high-frequency coefficient. Then entropy encoding was combined to implement lossless image compression. Experimental results show that IWLCA has high encoding efficiency, which can also effectively reduce encoding bit rate of lossless image compression. Compared with mainstream lossless algorithms as JPEG-LS and JPEG 2000, the compression rate was significantly improved. (C) 2013 Elsevier GmbH. All rights reserved.