Real Time Image Enhancement Using Texture Synthesis ( RETS )

Abstract

87 Abstract—Real time Enhancement using texture synthesis combines interpolation, classification and patch based texture synthesis to enhance low resolution imagery. RETS uses a low resolution source image as input and several high resolution sample textures. The output of RETS is a high resolution image with the structure of the source image, but with detail consistent with the high resolution sample textures. Image Interpolation: Interpolation is the primary technique used for image scaling. Image scaling is the process of taking a source image and extending it to create a large image. The primary problem with enlarging images using interpolation is that the large result contains the same amount of discrete data as smaller source image [25]. Two types of interpolation are bilinear and bicubic. Bilinear interpolation uses 2x2 neighbourhoods of data points to calculate pixel color between data points. Bicubic interpolation uses 4x4 neighbourhoods of data points to calculate pixel color between data points [16].Using texture Synthesis solve two problems

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Cite this paper

@inproceedings{Bhatt2012RealTI, title={Real Time Image Enhancement Using Texture Synthesis ( RETS )}, author={Parth Bhatt and Ankit Shah and Sunil Pathak}, year={2012} }