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Color space influence on mean shift filtering
Authors
H. Benoit-Cattin
T Grenier
T Li
Publication date
1 January 2011
Publisher
HAL CCSD
Abstract
International audienceMean shift is an efficient filtering algorithm processing multidimensional data as color images. Such algorithm needs few tuning parameters named scale parameters. In this paper, we study the impact of the color space used on the results quality. Two linear transformations of the RGB space (Y\textquoterightUV and PC A) and a non linear one (L*a*b* color space) are addressed. The results quality is assessed using the PSNR and the SSIM, a consistent measure with human eye perception. To determine the optimal color space, we use an exhaustive search of the scale parameters. This study reminds that PC A transformation is useless for mean shift and shows (using 5 natural color images and 2 synthesized data) that optimizing the bandwidth parameters in the L*a*b* space helps in improving the mean shift filtering assessed by PSNR. © 2011 IEEE
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oai:HAL:hal-01871243v1
Last time updated on 23/03/2021
Archive Ouverte en Sciences de l'Information et de la Communication
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HAL-UJM
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oai:HAL:hal-01871243v1
Last time updated on 18/09/2018