2000 Fiscal Year Final Research Report Summary
Image Enhancement using Perturbed Sub-block Phase-only Synthesis
| Project/Area Number |
11650387
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
情報通信工学
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| Research Institution | Kyushu Institute of Technology |
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Principal Investigator |
KONDO Hiroshi Kyushu Institute of Technology, Faculty of Engineering, Associate Professor, 工学部, 助教授 (80093962)
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| Project Period (FY) |
1999 – 2000
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| Keywords | Image Restoration / Fourier phase / Point spread function / Recursive filter / Deblurring |
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| Research Abstract |
New image enhancement technique is constructed. The perturbed phase-only synthesis (POS) developed here is utilized in this technique. As an application example we present an innovating inverse image restoration filter with a perturbed phase-only synthesis enhancement. Strictly speaking, almost all camera lenses including zoom lenses are of special variant. Hence a spatial variant filter is needed for restoring the image. We have developed a spatial variant image restoration filter with an innovating estimation of the point spread function (PSF). The figure of a real lens PSF has been checked in detail and the nature of a real lens PSF is used for estimation of it. The cost function for the PSF estimation is a sharpness of the image edge line in the phase-only synthesis. Once if the POS was estimated the optimal image restoration filter can be designed easily. However an image restoration filter does not always give a satisfactory result because of the compatibility between deblurring and denoising. In this work we construct an image edge sharpening for the restored image as a post processing. Usually sharpening is not so effective for the restored image because it increases a noise suppressed by a restoration filter. But it is not the case here due to the perturbed POS.The perturbed POS has an edge sharpening nature with suppressing noise. Hence it is very effective foe almost all image restoration filters. The simulation examples show us that it is just much to the restoration filter.
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