Data compression using adaptive bit allocation and hybrid lossless entropy encoding

摘要

A method and apparatus for adaptive bit allocation and hybrid lossless entropy encoding in a lossy compression system. The invention includes three components: (1) a transform stage to decorrelate image data into a baseband and multiple subbands, (2) a quantization stage to quantize the resulting transform coefficients, and (3) a lossless entropy coder stage to encode the quantized indexes. In the preferred embodiment, the transform stage uses a wavelet transform algorithm. The quantization stage adaptively estimates values for parameters defining an approximation between quantization size and the logarithm of quantization error, and recursively calculates the optimal quantization size for each band to achieve a desired bit rate. The baseband and subbands are transformed into quantization matrices using the corresponding quantization sizes. The lossless entropy coder stage uses the observation that the entropy property of run lengths of zero index values in the subband quantization matrices is different from the entropy property of non-zero indices. Each quantization matrix is parsed so that each non-zero index is extracted into a separate stream, and the remaining position information is parsed into an odd stream of run length values for "0" and an even stream of run length values for "1". These three streams are Huffman coded separately in conventional fashion. This hybrid algorithm gives an approximately 10% percent improvement over conventional run length and Huffman coding for similar images. The overall compression algorithm gives about 2 DIFFERENCE 6 dB improvement in terms of peak signal-to-noise ratio (PSNR) over JPEG algorithms for similar images at similar bit rates.