Title :
Vectorized total variation defined by weighted L infinity norm for utilizing inter channel dependency
Author :
Miyata, T. ; Sakai, Yoshiki
Author_Institution :
Tokyo Inst. of Technol., Tokyo, Japan
fDate :
Sept. 30 2012-Oct. 3 2012
Abstract :
Vectorized total variation (VTV) is very successful convex regularizer to solve various color image recovery problems. Despite the fact that color channels of natural color images are closely related, existing variants of VTV can not utilize this prior efficiently. We proposed L∞-VTV as a convex regularizer can penalize the violation of such inter-channel dependency by employing weighted L∞ (L-infty) norm. We also introduce an effective algorithm for an image denoising problem using L∞-VTV. Experimental results shows that our proposed method can outperform the conventional methods.
Keywords :
convex programming; image colour analysis; image denoising; variational techniques; L∞-VTV; color channels; color image recovery problem; convex regularizer; image denoising; interchannel dependency; natural color image; vectorized total variation; weighted L∞ norm; Abstracts; Jacobian matrices; PSNR; Total variation; color image processing; image denoising; optimization;
Conference_Titel :
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4673-2534-9
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2012.6467545