Evaluation of Region-of-Interest coders using perceptual image quality assessments

摘要

A perceptual measure emulates the human vision for image quality assessment. This paper illustrates the evaluation of Region-of-Interest (ROI) coders using perceptual image quality assessments. The goal of this evaluation is to characterize the coder performance by controlling the ROI quality. Perceptual measures are taken into account for evaluation since they behave as a human-made evaluation. Moreover, a perceptual assessment named Wavelet Quality Index (WQI), is introduced as another image coder evaluator. Proposed assessment aims at emulating the human vision by a weighted linear combination of three wavelet-based perceptual measures. We evaluate the following types of ROI-coders: those preserving the quality of ROI by coarse compression of background (Max-Shift coder), and those balancing the quality between ROI and background (SCM-Shift, and BbB-Shift coders). Using considered assessments for the performance evaluation of coders, results show a variation of evaluation by nature of measurement.