Open AccessModel for smoothing and segmentation of texture images using L 0 norm
Author(s) -
Badshah Noor,
Shah Hassan
Publication year - 2018
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2017.0136
Subject(s) - smoothing , segmentation , computer science , artificial intelligence , image texture , norm (philosophy) , computer vision , image segmentation , texture (cosmology) , pattern recognition (psychology) , scale space segmentation , image (mathematics) , political science , law
Segmentation of texture images is always a challenging problem in image processing. The authors propose a novel model for segmentation of texture images based on L 0 gradient norm. The model will do smoothing of texture in image and segmentation jointly. It is well known that L 0 gradient norm smooths the image and preserve the edges. Keeping this in view, the proposed model is using L 0 gradient norm for smoothing of texture in image and Chan–Vese energy for segmentation. For fast and efficient solution of the model, the authors use alternating minimisation algorithm. Experimental results of their proposed model, which are compared with well‐known (state of the art) existing models, validate better performance of the proposed model.