An integrated method for image compression using the discrete wavelet transform

Abstract

In this paper, we propose an integrated image compression method, which contains the discrete wavelet transform, scalar quantization and some lossless codings, to gain higher compression ratios while maintaining the image fidelity. The discrete wavelet transform, a multiresolution technique, has the properties of entropy reduction and energy concentration in high frequency subimages. Scalar quantizer is applied to high frequency components since those histograms can be modelled for the generalized Gaussian distribution. These subimages with small relative energy can be dropped entirely to compensate the compression ratio if the optimal scalar quantization is adopted. An innovative approach, named as revised run-length coding, is proposed to improve the compression performance. The idea of this approach is to represent the appearance of symbols of run-length codes in exponential expression for saving the storage in bits. One coding method, differential pulse coded modulation, is introduced to reduce the entropy of the lowest frequency subimage performed after the discrete wavelet transform and to achieve the high compression effect losslessly. The experimental results are compared with some well-known methods, for example, JPEG, (entropy constrained) vector quantization, fractal-based compression method and wavelet with variable-length coding.