DocumentCode :
3778248
Title :
Exemplar-based image inpainting algorithm using adaptive sample and candidate patch system
Author :
Fan Qian; Zhang Lifeng; Hu Xuelong
Author_Institution :
Department of Electrical Engineering and Electronics, Kyushu Institute of Technology, Fukuoka 804-0015, Japan
Volume :
3
fYear :
2015
fDate :
7/1/2015 12:00:00 AM
Firstpage :
1219
Lastpage :
1223
Abstract :
In the existing exemplar based image inpainting algorithms, the most similar match patches are used to inpaint the destroyed region, and they are searched in the whole source region in a fixed size. However, sometimes it would decrease the connectivity of structure and clearness of texture while increases the time complexity of this algorithm. To solve these problems, firstly it proposed an adaptive sample algorithm based on patch sparsity, it calculates the patch sparsity and through it dividing the patches location into three types. And then the size of the sample patch would be adaptively changed according to the type. Secondly it proposed a candidate patch system to improve the patch matching rate. From the result, we can see that the proposed method can match more significant patches than the traditional method, and it can give a better texture inpainting effect, especially when processing the images with complex and regular textures, and the image with large destroyed region.
Keywords :
"Biographies","Sensors"
Publisher :
ieee
Conference_Titel :
Electronic Measurement & Instruments (ICEMI), 2015 12th IEEE International Conference on
Type :
conf
DOI :
10.1109/ICEMI.2015.7494492
Filename :
7494492
Link To Document :
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