Title :
Images Restoration Using an Iterative Dynamic Programming Approach
Author_Institution :
Laurentian Univ., Sudbury
Abstract :
A novel image restoration algorithm is presented in this paper. The restoration problem is formulated under the energy minimization framework and is solved using a dynamic programming-based approach. Through applying dynamic programming iteratively along both horizontal and vertical scanlines, the new algorithm can quickly converge to a near-global-optimal solution, without suffering the so-called streak artifacts. Experiments on both grayscale and color images demonstrate that the presented algorithm can effectively remove Gaussian noise and impulse noise from corrupted images, as well as to restore images with missing intensity values.
Keywords :
Gaussian noise; dynamic programming; image colour analysis; image denoising; image restoration; impulse noise; minimisation; Gaussian noise; color images; energy minimization framework; image restoration; impulse noise; iterative dynamic programming; missing intensity values; near-global-optimal solution; streak artifacts; Color; Colored noise; Costs; Dynamic programming; Gaussian noise; Gray-scale; Image converters; Image restoration; Iterative algorithms; Iterative methods; Image restoration; dynamic programming.; global optimization;
Conference_Titel :
Computer and Robot Vision, 2007. CRV '07. Fourth Canadian Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
0-7695-2786-8
DOI :
10.1109/CRV.2007.40