AN EFFECTIVE IMAGE DEBLURRING SCHEME USING CLUSTER BASED SPARSE REPRESENTATION

Authors

  • Yediga Ravi Sankaraiah Department of Electronics and Communication Engineering, Jawaharlal Nehru Technological University, Kakinada, India
  • Sourirajan Varadarajan Department of Electronics and Communication Engineering, Jawaharlal Nehru Technological University, Kakinada, India

DOI:

https://doi.org/10.11113/aej.v11.17861

Keywords:

Cluster of patches, Image restoration, Mixed blur, Self-similarity, Sparse coding

Abstract

Sparse based representation is being used extensively for image restoration. The dictionary learningthrough patch extraction is central to the sparse based schemes. In the process of dictionary learning,a large number of patches will be extracted from high quality images and dictionary will be formed.Hence, over-complete dictionaries will be built. To overcome the complexity associated with overcompletedictionaries many schemes were proposed. Of them, the adaptive sparse domain is thepopular one. Many variations of adaptive sparse domain schemes were proposed. Selection of obviouspatches is common to all. In all these schemes, individual patches will be considered as the basic entityand will be used. This is the reason for the complexity involved in sparse representation. In this paper,to avoid the complexity, the patches are grouped according to the similarity among the patches. Inaddition to reduce the complexity the proposed cluster based scheme considers the self-similarity ofthe patches involved. Hence better performance with less complexity is possible with the proposedschemes. In the process of testing, in addition to uniform blur and Gaussian blur, a combination of thetwo blurs is also considered.

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Published

2021-10-26

How to Cite

Sankaraiah, Y. R. ., & Varadarajan, S. . (2021). AN EFFECTIVE IMAGE DEBLURRING SCHEME USING CLUSTER BASED SPARSE REPRESENTATION. ASEAN Engineering Journal, 11(4), 16-28. https://doi.org/10.11113/aej.v11.17861