An amended Joint Super-Resolution and Deblocking for a  Compressed Images

An amended Joint Super-Resolution and Deblocking for a Compressed Images
Author(s):
V.Sujini Goud
Keywords:
Image super-resolution, sparse representation,dictionary learning, self-learning, image decomposition
Abstract
Super-resolution imaging (SR) is a class of techniques that improve the resolution of an imaging system. A highly compressed image is typically not only of lowresolution, but also undergoes from compression artifacts. In this paper, we suggest a learning-based framework to accomplish joint single-image SR and deblocking for a highly-compressed image. We say that individually performing deblocking and SR (i.e., deblocking followed by SR, or SR followed by deblocking) on a highly compressed image usually cannot achieve a satisfactory visual quality. In our method, we suggest to learn image sparse representations for modeling the relationship between low and high-resolution image patches in terms of the learned dictionaries for image patches with and without blocking artifacts, respectively.
Article Details
Unique Paper ID: 143621 Publication Volume & Issue: Volume 2, Issue 12 Page(s): 453 - 456
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