Title :
Perceptual Saliency Driven Total Variation for Image Denoising Using Tensor Voting
Author :
Xiao, Liang ; Huang, Lili ; Zhang, Fanbiao
Author_Institution :
Sch. of Comput. Sci., Nanjing Univ. of Sci. & Technol., Nanjing, China
Abstract :
A nature image often contains various regions such as flat regions, ramps and edges with different singularities. A new perceptual saliency indicator is firstly proposed to distinguish edges and ramps. The proposed indicator is designed by a tensor voting approach with perceptual grouping performance. Using the perceptual saliency indicator, we propose a new variational model with an adaptive regularization term and a saliency weighted fidelity term. Experimental results demonstrate that our method has better performance in the staircase effect alleviation, the ramps and ridges preserving when compared with the state-of-the-art.
Keywords :
image denoising; natural scenes; image denoising; nature image; perceptual saliency driven total variation; perceptual saliency indicator; ramps preserving; ridges preserving; staircase effect alleviation; tensor voting; Adaptation models; Image edge detection; Mathematical model; Noise; Noise reduction; Tensile stress; Transforms; adaptive regularization; image denosing; perceptual saliency indicator; tensor voting;
Conference_Titel :
Image and Graphics (ICIG), 2011 Sixth International Conference on
Conference_Location :
Hefei, Anhui
Print_ISBN :
978-1-4577-1560-0
Electronic_ISBN :
978-0-7695-4541-7
DOI :
10.1109/ICIG.2011.75