Name
Abstract | ||
|---|---|---|
We derive a visual image quality metric from a model of human visual processing that takes as its input an original image and a compressed or otherwise altered version of that image. The model has multiple channels tuned to spatial frequency, orientation and color. Channel sensitivities are scaled to match a bandpass achromatic spatial frequency contrast sensitivity function (CSF) and lowpass chromatic CSFs. The model has a contrast gain control with parameters based on the results of human psychophysical experiments on pattern masking and contrast induction. These experiments have shown that contrast gain control within the visual system is selective for spatial frequency, orientation and color. The model accommodates this result by placing a contrast gain control within each channel and by letting each channel's gain control be influenced selectively by contrasts within all channels. A simple extension to this model provides predictions of color image quality. |
Year | DOI | Venue |
|---|---|---|
1998 | 10.1117/12.320111 | HUMAN VISION AND ELECTRONIC IMAGING III |
Keywords | Field | DocType |
color, contrast gain control, image quality | Computer vision,Chromatic scale,Masking (art),Optics,Image quality,Image processing,Artificial intelligence,Automatic gain control,Color vision,Spatial frequency,Color image,Physics | Conference |
Volume | ISSN | Citations |
3299 | 0277-786X | 2 |
PageRank | References | Authors |
0.68 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael D'Zmura | 1 | 55 | 6.25 |
| tsaepyng j shen | 2 | 2 | 0.68 |
| wei wu | 3 | 2 | 0.68 |
| Homer H Chen | 4 | 1017 | 90.44 |
| M. Vassiliou | 5 | 16 | 5.11 |