TY - CONF
T1 - Color space influence on mean shift filtering
T2 - Proceedings - International Conference on Image Processing, ICIP
Y1 - 2011
A1 - Li, T
A1 - T Grenier
A1 - Benoit-Cattin, H.
KW - Algorithms
KW - categ_st2i
KW - Color image processing
KW - Data handling
KW - Images et ModÃ¨les
KW - Linear transformations
KW - Mathematical transformations
KW - Metadata
KW - Optimization
AB - Mean 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'UV 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.
JF - Proceedings - International Conference on Image Processing, ICIP
CY - Brussels, Belgium
UR - http://dx.doi.org/10.1109/ICIP.2011.6115720
ER -