Authors:
Rajesh Bhatt
and
Venkatesh K. Subramanian
Affiliation:
Indian Institute of Technology Kanpur, India
Keyword(s):
Sparse Representation, Clustering, PCA, De-noising, Signal Reconstruction.
Related
Ontology
Subjects/Areas/Topics:
Informatics in Control, Automation and Robotics
;
Optimization Problems in Signal Processing
;
Signal Processing, Sensors, Systems Modeling and Control
;
Signal Reconstruction
Abstract:
Sparse representation based image and video processing have recently drawn much attention. Dictionary
learning is an essential task in this framework. Our novel proposition involves direct computation of the
dictionary by analyzing the distribution of training data in the metric space. The resulting representation is
applied in the domain of grey scale image denoising. Denoising is one of the fundamental problems in image
processing. Sparse representation deals efficiently with this problem. In this regard, dictionary learning from
noisy images, improves denoising performance. Experimental results indicate that our proposed approach
outperforms the ones using K-SVD for additive high-level Gaussian noise while for the medium range of
noise level, our results are comparable.