Application of LUM filters with automatic parameter selection to edge detection

M. Miloslavski; Tae-Sun Choi

doi:10.1117/12.323156

1 October 1998 Application of LUM filters with automatic parameter selection to edge detection

M. Miloslavski, Tae-Sun Choi

Proceedings Volume 3460, Applications of Digital Image Processing XXI; (1998) https://doi.org/10.1117/12.323156
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

Abstract

This paper examines the use of nonlinear order-based filter, LUM filter as a prefilter for gradient edge detectors. The output of this filter is an order statistic from an observation vector. Wide range of characteristics can be achieved with the same filter structure by changing its parameters. Its ability to suppress impulse noise and enhance edges leads to significant improvement in edge map. An algorithm for automatic filter parameters adjustment is proposed based on the impulse noise level identification. Algorithm efficiency to set optimal parameters is demonstrated. Its accuracy in determining noise level is evaluated and drawbacks are discussed.

Citation Download Citation

M. Miloslavski and Tae-Sun Choi "Application of LUM filters with automatic parameter selection to edge detection", Proc. SPIE 3460, Applications of Digital Image Processing XXI, (1 October 1998); https://doi.org/10.1117/12.323156

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