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Technical Program
Paper Detail
| Paper: | WP-L3.8 |
| Session: | Image Enhancement and Artifact Reduction |
| Time: | Wednesday, October 11, 17:00 - 17:20 |
| Presentation: |
Lecture
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| Title: |
GRADIENT ADAPTIVE IMAGE RESTORATION AND ENHANCEMENT |
| Authors: |
Hongcheng Wang; University of Illinois at Urbana-Champaign | | | | | Yunqiang Chen; Siemens Corporate Research, Inc. | | | | | Tong Fang; Siemens Corporate Research, Inc. | | | | | Jason Tyan; Siemens Corporate Research, Inc. | | | | | Narendra Ahuja; University of Illinois at Urbana-Champaign | | |
| Abstract: |
Various methods have been proposed for image enhancement and restoration. The main difficulty is how to enhance the structures uniformly while suppressing the noise without artifacts. In this paper, we tackle this problem in the gradient domain instead of the traditional intensity domain. By enhancing the gradient field, we can enhance the structure uniformly without overshooting at the boundary. Because the gradient field is very sensitive to noise, we apply an orientation-isotropy adaptive filter to the gradient field, suppressing the gradients in the noise regions while enhancing along the object boundaries. Thus we obtain a modulated gradient field, which is usually not integrable. We reconstruct the enhanced image from the modulated gradient field with least square errors by solving a Poisson equation. This method can enhance the object contrast uniformly, suppress the noise with no artifacts, and avoid setting stopping time as in PDE methods. Experiments on noisy images show the efficacy of our method. |
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