Title :
An improved exemplar-based image inpainting algorithm
Author :
Chunyang Xiang ; Pengsong Duan ; Yangjie Cao ; Lei Shi
Author_Institution :
Sch. of Inf. Eng., Zhengzhou Univ., Zhengzhou, China
Abstract :
Aiming to address deficiencies existing in traditional image inpainting algorithms, an improved image inpainting algorithm, named S-Criminisi, is proposed. Compared with traditional image inpainting algorithms, advantages of S-Criminisi are: (1) Instead of using traditional curve fitting method, S-Criminisi utilizes the Difference Method calculating gradient operator and obtaining curvature of target point; (2) To solve discontinuities of visual images caused by error matching, a new matching method based on matrix similarity is applied by S-Criminisi. Experimental results show that S-Criminisi is more suited for characteristics of digital image and be a better solution for discontinuities of visual images.
Keywords :
curve fitting; image matching; matrix algebra; S-Criminisi algorithm; curve fitting method; difference method; exemplar-based image inpainting algorithm; gradient operator; matching method; matrix similarity; target point curvature; visual image discontinuity; Computers; Filling; Lead; PSNR; TV; Difference Method; exemplar block; image inpainting;
Conference_Titel :
Computer Science & Education (ICCSE), 2014 9th International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
978-1-4799-2949-8
DOI :
10.1109/ICCSE.2014.6926566