1 January 2005 Multiscale image sharpening adaptive to edge profile
Hiroaki Kotera, Wang Hui
Author Affiliations +
Abstract
The color image has different edge profiles depending on the objects placed in the scene. We propose a novel image-sharpening method adaptive to the local edge slopes with the suppression of background noises. Prescanning the image by a Gaussian derivative (GD) filter, we generate the edge map, which classifies the edge areas to hard, medium, and soft edges, and separates the flat areas without edges. Multiple GD filters with different standard deviations are selectively applied to sharpen each segmented edge area by looking up the edge map. To keep the gray balance, the edge-sharpening filters are applied only to the luminance image. In flat areas except edges, the sharpening filters are resumed and instead, a Gaussian smoothing filter is applied to reduce the background noises. The proposed method brings a dramatic improvement in the reduction of flat-area noises and the natural image-sharpening effects adaptive to the edge slopes. In addition, we newly introduce quality assessment indices to evaluate the image sharpness and flat-area noises with the experimental data.
©(2005) Society of Photo-Optical Instrumentation Engineers (SPIE)
Hiroaki Kotera and Wang Hui "Multiscale image sharpening adaptive to edge profile," Journal of Electronic Imaging 14(1), 013002 (1 January 2005). https://doi.org/10.1117/1.1866147
Published: 1 January 2005
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CITATIONS
Cited by 18 scholarly publications.
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KEYWORDS
RGB color model

Image filtering

Image enhancement

Digital filtering

Visual process modeling

Image processing

Smoothing

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