Identification and Removal of Impulsive Noise from Corrupted Images Using Hypergraph Model

D. Aradhana *

Ballari Institute of Technology and Management, Bellary, Karnataka, India

K. G. Karibasappa

B.V.B.College of Engineering & Technology, Hubli-31, Karnataka, India

A. Channa Keshav Reddy

Jawaharlal Nehru Technological University, Hyderabad, Andhra Pradesh, India

K. Karibasappa

Dayanand Sagar College of Engineering, Bangalore, Karnataka, India

*Author to whom correspondence should be addressed.


Abstract

Image noise is unwanted information of an image. Noise can occur during image capture, transmission, or processing and it may depend or may not depend on image content. In order to remove the noise from the noisy image, prior knowledge about the nature of noise must be known otherwise noise removal causes the image blurring. Identifying nature of noise is a challenging problem. Many researchers have proposed their ideas on image denoising and each of them has its assumptions, advantages and limitations. In this paper, we are proposing a new algorithm for identifying and removing the impulsive noise using hypergraph concept.

Keywords: Hypergraph, noise, neighborhood, segmentation, homogeneous regions;


How to Cite

Aradhana, D., K. G. Karibasappa, A. Channa Keshav Reddy, and K. Karibasappa. 2011. “Identification and Removal of Impulsive Noise from Corrupted Images Using Hypergraph Model”. Journal of Advances in Mathematics and Computer Science 1 (2):112-20. https://doi.org/10.9734/BJMCS/2011/189.

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