Title :
Image inpainting and image denoising in wavelet domain using fast curve evolution algorithm
Author :
Dhiyanesh, B. ; Sathiyapriya, K.S.
Author_Institution :
CSE, Nehru Inst. Of Eng. & Technol., Coimbatore, India
Abstract :
Image denoising refers to removal of noise from an image and the problem of filling the missing coefficients in an image is known as inpainting. In traditional system, the damaged image is used to restore the missing coefficients by pixel domain. The total variation (TV) minimization wavelet models is used for the problem of missing or damaged wavelet coefficients due to lossy image transmission or communication and show TV minimization is convergent. In this paper, active contour/snake model is one of the most successful variation models in image segmentation. It consists of evolving a contour in image toward the boundary of objects. Its success is based on strong mathematical properties and efficient numerical schemes based on the level set method.
Keywords :
curve fitting; image denoising; image restoration; image segmentation; minimisation; visual communication; wavelet transforms; TV minimization wavelet model; active contour-snake model; damaged image; damaged wavelet coefficient problem; fast curve evolution algorithm; image denoising; image inpainting; image restoration; image segmentation; level set method; lossy image communication; lossy image transmission; missing coefficient filling; missing wavelet coefficient problem; noise removal; pixel domain; total variation minimization wavelet model; variation models; Image edge detection; Image reconstruction; Image resolution; Indexes; Mathematical model; Numerical models; TV; Contours; Denoising; Evolution and Segmentation; Total Variation Minimization; Variation; Wavelet;
Conference_Titel :
Advanced Communication Control and Computing Technologies (ICACCCT), 2012 IEEE International Conference on
Conference_Location :
Ramanathapuram
Print_ISBN :
978-1-4673-2045-0
DOI :
10.1109/ICACCCT.2012.6320763
