IMAGE QUALITY MEASURES FOR WAVELET-BASED COMPRESSION ALGORITHMS

In this paper, three full-reference metrics for image quality assessment are presented. They are based on the Peak-Signal-to-Noise Ratio (PSNR), static characteristics, singular value decomposition (SVD) modified to take into account the Human Visual System (HVS) properties. Many studies confirm that the HVS is more sensitive to low frequency distortions rather than to high frequency ones [1]. To test the effectiveness of the proposed metrics, we have performed a subjective experiment. In our experiment we have used Wavelet decomposed images, using different filters, bitrates and conpressed algorithms. The analysis of the results shows that the proposed PSNR-HVS provides better correlation to Mean Observer Score (MOS). Using the best criterium we have performed a comparative analysis of the wavelet-based compression algorithms and the analysis of the filters