Open AccessImage Inpaint Using Patch Sparsity
Author(s) -
Shital D. Suryawanshi,
P. V. Baviskar
Publication year - 2020
Publication title -
aptikom journal on computer science and information technologies
Language(s) - English
Resource type - Journals
eISSN - 2528-2425
pISSN - 2528-2417
DOI - 10.34306/csit.v1i3.54
Subject(s) - inpainting , texture synthesis , image (mathematics) , artificial intelligence , pixel , computer vision , process (computing) , computer science , object (grammar) , image texture , digital image , texture (cosmology) , algorithm , mathematics , pattern recognition (psychology) , image processing , operating system
The process of removing the specific object or area or repairing the damaged area in an image is known as image inpainting. This algorithm [5] is proposed for removing objects from digital image. The challenge is to fill in the hole that is left behind in a visually plausible way. We first note that patch sparsity based synthesis contains the essential process required to replicate both texture and structure [8]; the success of structure propagation however is highly dependent on the order in which the filling proceeds. We propose a best algorithm in which the confidence in the synthesized pixel values is propagated in a manner similar to the propagation of information in inpainting.The actual color values are computed using patch sparsity based synthesis. In this paper the simultaneous propagation of texture and structure information [2] is achieved by a single, efficient algorithm. For best results selected image should have sufficient background information