DocumentCode
3271643
Title
Local weighted Gaussian curvature for image processing
Author
Yuanhao Gong ; Sbalzarini, Ivo F.
Author_Institution
Center of Syst. Biol., Max Planck Inst. of Mol. Cell Biol. & Genetics, Dresden, Germany
fYear
2013
fDate
15-18 Sept. 2013
Firstpage
534
Lastpage
538
Abstract
We present a variational model with local weighted Gaussian curvature as regularizer. We show its convexity for an area-weight function and provide a closed-form solution for this case. The corresponding regularization coefficient has a theoretical bound. Moreover, we prove that the model is convex for a wide range of weight functions and show that it can be efficiently solved using splitting techniques. Finally, we demonstrate several applications of the model in image de-noising, smoothing, texture decomposition, image sharpening, and regularization-coefficient optimization.
Keywords
Gaussian processes; convex programming; image denoising; image texture; smoothing methods; variational techniques; area-weight function; closed-form solution; convex model; image denoising; image processing; image sharpening; image smoothing; local weighted Gaussian curvature; regularization coefficient; regularization-coefficient optimization; splitting techniques; texture decomposition; variational model; weight functions; Approximation methods; Closed-form solutions; Computational modeling; Manganese; Mathematical model; Smoothing methods; TV; Gaussian curvature; convex model; image processing; regularization; variational form;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2013 20th IEEE International Conference on
Conference_Location
Melbourne, VIC
Type
conf
DOI
10.1109/ICIP.2013.6738110
Filename
6738110
Link To Document