DocumentCode
595294
Title
Contrast-enhancing seam detection and blending using graph cuts
Author
Weibel, Thomas ; Daul, Christian ; Wolf, Denis ; Rosch, R.
Author_Institution
CRAN, Univ. de Lorraine, Vandœuvre-Lès-Nancy, France
fYear
2012
fDate
11-15 Nov. 2012
Firstpage
2732
Lastpage
2735
Abstract
During the image placement onto the compositing surface (mosaic), stitching algorithms try to minimize visual inconsistencies (texture discontinuities), seam induced color gradients, and blurry image regions. These problems are classically processed separately. In this contribution, we describe a two step graph-cut algorithm that combines these issues. In the first step, optimal seam locations are detected while maximizing the contrast of the mosaic. The second step corrects vignetting and exposure differences along the previously determined seams while retaining contrast, hue and saturation of the images. Qualitative and quantitative results demonstrates that the proposed method produces exposure corrected mosaics that are locally sharper than the individual images from the sequence.
Keywords
gradient methods; graph theory; image colour analysis; image enhancement; image segmentation; image sequences; image texture; minimisation; blurry image regions; contrast-enhancing seam detection; exposure differences; image contrast; image hue; image placement; image saturation; image sequence; mosaic contrast maximization; optimal seam location detection; seam induced color gradients; stitching algorithms; texture discontinuities; two step graph-cut algorithm; visual inconsistency minimization; Bladder; Cancer; Endoscopes; Image color analysis; Laplace equations; Optimization; Pattern recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location
Tsukuba
ISSN
1051-4651
Print_ISBN
978-1-4673-2216-4
Type
conf
Filename
6460730
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