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 Algo-rithm (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.-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　Algo-rithm　 (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.