Hybrid image compression scheme based on wavelet transform and adaptive context modeling
Abstract
A hybrid image compression scheme based on wavelet transform, HVS thresholding and L∞-constrained adaptive context modelling is proposed. This hybrid system combines the strengths of the wavelet transform, the HVS thresholding and the adaptive context modelling to result in a near optimal compression scheme. In the scheme, the image is first decomposed into the multiresolution subimages using the orthogonal wavelet transform; each subimage corresponds to a octave band in the wavelet decomposition. The coefficients in the high-pass octave bands of the wavelet transform are then quantized through HVS frequency- and spatial model-based thresholding and vector quantization into wavelet decomposition with only significant coefficients to the HVS retained. It is demonstrated that the hybrid scheme is one of the best compression schemes in achieving the excellent compression rates and competitive PSNR while maintaining a small visual distortion.