ADAPTIVE NONLINEAR IMAGE ENHANCEMENT OF GAUSSIAN DEGRADED IMAGES
| Autor: | Yue Yang, Baoxin Li, Shalin Mehta, Rahul Gowda |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
business.industry
Gaussian ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Gaussian blur Computer Graphics and Computer-Aided Design Computer Science Applications Image (mathematics) Nonlinear system symbols.namesake Gabor filter Compression (functional analysis) symbols Computer vision Computer Vision and Pattern Recognition Digital television Artificial intelligence business Image restoration Mathematics |
| Zdroj: | International Journal of Image and Graphics. 10:365-393 |
| ISSN: | 1793-6756 0219-4678 |
| DOI: | 10.1142/s0219467810003822 |
| Popis: | An adaptive technique for nonlinear image enhancement using Gabor filters is proposed. A set of Gabor filters are employed to extract high-pass components from the blurred image and these components are then nonlinearly processed before adding back to the input image for enhancement. Further, we propose a novel method for fast blur estimation and we establish an empirical relationship between the estimated blur and the optimal Gabor filter parameters, resulting in an enhancement system that is adaptive to the degree of blur in the input image. Extensive evaluation, including both PSNR-based objective evaluation and subjective psychophysical tests, confirms the advantages of the proposed approach over existing state-of-the-art methods. This enhancement approach is especially targeted at digital television applications where image blur is present due to various reasons like compression and resolution up-conversion. |
| Databáze: | OpenAIRE |
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