Efficient detail-preserving method of impulse noise removal from highly corrupted images

Sanjit K. Mitra; Tian-Hu Yu; Rosalizah Ali

doi:10.1117/12.171090

23 March 1994 Efficient detail-preserving method of impulse noise removal from highly corrupted images

Sanjit K. Mitra, Tian-Hu Yu, Rosalizah Ali

Proceedings Volume 2182, Image and Video Processing II; (1994) https://doi.org/10.1117/12.171090
Event: IS&T/SPIE 1994 International Symposium on Electronic Imaging: Science and Technology, 1994, San Jose, CA, United States

Abstract

Images are often corrupted by impulse noise due to faulty image acquisition devices or during transmission. The goal of impulse noise removal is to suppress the noise while preserving edges and details. In this paper, an efficient method is proposed to remove impulse noise from a highly corrupted image while preserving the detail features. This new method is based on a detection-estimation strategy, in which the impulse noise is detected first using a quadratic filter, and a selectively chosen local mean is used to estimate the true value of the corrupted pixel. Simulation results indicate that the new method is much more efficient and effective than the median filtering and the out-range methods.

Citation Download Citation

Sanjit K. Mitra, Tian-Hu Yu, and Rosalizah Ali "Efficient detail-preserving method of impulse noise removal from highly corrupted images", Proc. SPIE 2182, Image and Video Processing II, (23 March 1994); https://doi.org/10.1117/12.171090

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available