TY - GEN
T1 - A generalized vector-valued total variation algorithm
AU - Rodríguez, Paul
AU - Wohlberg, Brendt
PY - 2009
Y1 - 2009
N2 - We propose a simple but flexible method for solving the generalized vector-valued TV (VTV) functional, which includes both the ℓ2-VTV and ℓ1-VTV regularizations as special cases, to address the problems of deconvolution and denoising of vector-valued (e.g. color) images with Gaussian or salt-and-pepper noise. This algorithm is the vectorial extension of the Iteratively Reweighted Norm (IRN) algorithm [1] originally developed for scalar (grayscale) images. This method offers competitive computational performance for denoising and deconvolving vector-valued images corrupted with Gaussian (ℓ2-VTV case) and salt-and-pepper noise (ℓ1-VTV case).
AB - We propose a simple but flexible method for solving the generalized vector-valued TV (VTV) functional, which includes both the ℓ2-VTV and ℓ1-VTV regularizations as special cases, to address the problems of deconvolution and denoising of vector-valued (e.g. color) images with Gaussian or salt-and-pepper noise. This algorithm is the vectorial extension of the Iteratively Reweighted Norm (IRN) algorithm [1] originally developed for scalar (grayscale) images. This method offers competitive computational performance for denoising and deconvolving vector-valued images corrupted with Gaussian (ℓ2-VTV case) and salt-and-pepper noise (ℓ1-VTV case).
KW - Color image processing
KW - Vector-valued total variation
UR - http://www.scopus.com/inward/record.url?scp=77951947392&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2009.5413587
DO - 10.1109/ICIP.2009.5413587
M3 - Conference contribution
AN - SCOPUS:77951947392
SN - 9781424456543
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 1309
EP - 1312
BT - 2009 IEEE International Conference on Image Processing, ICIP 2009 - Proceedings
PB - IEEE Computer Society
T2 - 2009 IEEE International Conference on Image Processing, ICIP 2009
Y2 - 7 November 2009 through 10 November 2009
ER -