Abstract
Image sharpness is one of the common metrics for image quality assessment. Existing sharpness metrics have not given enough consideration to the human luminance masking effect. The root mean squared contrast model is improved by considering the human luminance masking effect. A perceptual contrast model is presented. A no-reference sharpness metric is established by averaging the perceptual contrast over the region of interest (contains image details, edges, and texture). IVC database is used to test the proposed sharpness metric. Experimental results show that, compared with four existing sharpness (blur) metrics, the proposed perceptual sharpness metric provides better predictions which more closely matches to the human visual perception, and has lower computational complexity. The sharpness metric is simple but effective.
Original language | English |
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Pages (from-to) | 396-399 |
Number of pages | 4 |
Journal | Guangxue Jishu/Optical Technique |
Volume | 41 |
Issue number | 5 |
Publication status | Published - 1 Sept 2015 |
Keywords
- Human luminance masking effect
- Image contrast
- Image sharpness
- Objective evaluation