Nonlinear Deblurring Algorithm on Convex-Mirror Image for Reducing Occlusion


The KIPS Transactions:PartA, Vol. 13, No. 5, pp. 429-434, Oct. 2006
10.3745/KIPSTA.2006.13.5.429,   PDF Download:

Abstract

A CCTV system reduces some number of cameras if we use convex-mirror. In this case, convex-mirror image distorted, we need transformation to flat images. In the center of mirror images, a transformed image has no distortion, but at near boundary image has plentiful distortion. This distortion is caused by occlusion of angled ray and diffraction. We know that the linear filtering approach cannot separate noise from signal where their Fourier spectra overlap. But using a non-linear discretization method, we shall reduce blurred noise. In this paper, we introduce the backward solution of nonlinear wave equation for reducing blurred noise and biased expansion of equilibrium contour. We propose, after applying the introduced method, and calculate with discretization method. To analysis the experimental result, we investigate to PSNR and get about 4 dB better than current method.


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Cite this article
[IEEE Style]
I. J. Lee, "Nonlinear Deblurring Algorithm on Convex-Mirror Image for Reducing Occlusion," The KIPS Transactions:PartA, vol. 13, no. 5, pp. 429-434, 2006. DOI: 10.3745/KIPSTA.2006.13.5.429.

[ACM Style]
In Jung Lee. 2006. Nonlinear Deblurring Algorithm on Convex-Mirror Image for Reducing Occlusion. The KIPS Transactions:PartA, 13, 5, (2006), 429-434. DOI: 10.3745/KIPSTA.2006.13.5.429.