关键词: 半色调图像, 加网算法, 亮度, 纹理, 视觉相似

Abstract: To measure quality of halftones or halftoning algorithms, this paper proposed Mean Luminance Similarity Error (MLSE), Mean Contrast Similarity Error (MCSE) and Visual Perception Similarity Error (VPSE) to measure the visual perception similarity between halftones and their original continuous-tone images. In the proposed method, an input image was divided into several blocks according to local adaptation of human eyes, and luminance similarity error and contrast similarity error in each block were computed according to luminance adaptation and contrast masking on visual perception. Finally, the MLSE, MCSE and VPSE were computed to evaluate luminance similarity, texture similarity and local unexpected artifacts respectively. The experimental results show that the proposed quality measures are more agreeable to HVS in comparison with Peak Signal to Noise Ratio (PSNR) and Weighted Signal to Noise Ratio (WSNR) in terms of luminance similarity and in comparison with Unique Quality Index (QUI) and Structure Similarity Index Measure (SSIM) in terms of texture similarity.

Key words: halftone, halftoning algorithm, luminance, texture, visual perception similarity