PAPER ID:IJIM/V.2(VIII)/165-174/26

AUTHOR :Gurhans Pal and Er. Vikas Sharma

TITLE: DYNAMIC PATCH SELECTION IN IMAGE INPAINTING

ABSTRACT: The remarkable demand for universal distribution and consumption of image and video content over various networks has pressured the digital consumer electronics industry to launch an almost infinite variety of electronic devices capable of acquiring, processing, editing and storing these very attractive types of content. The combination of this trend with the increasing demand for higher qualities and larger screen resolutions has posed another challenging problem to the image coding research community: to significantly increase the current image compression efficiency for the various, relevant target qualities. In this context, better exploiting the Human Visual System behaviours and characteristics is largely recognized as an appealing way to target further improvements in terms of image compression efficiency. With this purpose in mind, inpainting-based image coding solutions have recently emerged as a novel coding paradigm to further exploit the imagevisualredundancy, thus allowing increasing the compression efficiency while assuring the required perceived image quality.we have developed a new method on the platform of gravitational search algorithm (GSA) optimisation and Markov Random Field optimised adaptive size blocking in image inpainiting. We replaced the complex MRF with a less complex and more approximate method GSA optimisation algorithm. The conducted performance evaluation shows that the developed inpainting-based image solution outperforms the previous method for the PSNR (peak signal to noise ratio), MSE (mean square error) and dissimilarity metric for all the selected test images, while significantly improves the solution, which is very encouraging.

KEYWORDS: GSA, MRF

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