Evaluation and comparison of techniques for reconstructing the point spread function of images blurred by uniform linear motion
Journal Title: TecnoLógicas - Year 2018, Vol 21, Issue 42
Abstract
In the field of digital image processing,it is common to find differenttypes of degradation.One of them is motion blur, which is caused by the relative movement between the camera and the observed object. Itproduces a low-contrast trace on the image that follows the trajectory of the movement. If the relative velocity is constant and the blur is invariant acrossthe entire image, the resulting blur can be modeled by means of the Point Spread Function (PSF)andusing the trace’s length and the angle parameters. This work evaluated the accuracy of the estimation of the angle and length parameters, and the robustness to Additive White Gaussian Noise of a set of spatial and frequency approaches for reconstructing the PSF. It is important to highlight that the algorithms’ processing time was also considered. In total, 20 512x512 pixelssynthetically-degraded images were used. Besides, five of the best-known techniques for estimating the angle and three for the length of the PSFwere evaluated. The experimental results revealed the techniques with thelowest absolute mean error for estimatingthe angle and the length of the PSF in noise-free images: 2D Cepstrum Transform and 1D Cepstrum Transform, respectively.
Authors and Affiliations
Jimmy A. Cortés-Osorio, Cristian D. López-Robayo, Nathalia Hernández-Betancourt
Keywords
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- EP ID EP336633
- DOI 10.22430/22565337.789
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