Recursive Multi-Directional Image Filters

Tu-Chih Tsai; Dimitris Anastassiou

doi:10.1117/12.976501

13 October 1987 Recursive Multi-Directional Image Filters

Tu-Chih Tsai, Dimitris Anastassiou

Proceedings Volume 0845, Visual Communications and Image Processing II; (1987) https://doi.org/10.1117/12.976501
Event: Cambridge Symposium on Optics in Medicine and Visual Image Processing, 1987, San Diego, CA, United States

Abstract

Recursive image filters are computationally more efficient than nonrecursive ones. The phase of recursive filters is normally nonlinear, but it can become linear (actually zero) by the use of multi-directional filtering, in which the overall system is a cascade or parallel combination of the same simple recursive filter applied in different directions. The same concept is generalized to include nonlinear recursive multi-directional image filters. Non-linear recursive filters have not been investigated in the literature due to their analytic difficulty and their lack of general stability criteria. A useful task requiring nonlinear operation is to differentiate the high spatial frequency components of a picture into those due to edges and those due to noise. A linear low-pass filter will simultaneously smooth noise and blur edges. A linear high-pass filter will simultaneously crisp edges and enhance noise. We propose a specific nonlinear multi-directional recursive scheme for simultaneous edge enhancement and noise smoothing of images. The filter has low complexity and is guaranteed to be stable. It can be used for image enhancement or restoration purposes, or as a pre-processor for spatial coding techniques, in which case the compression ratio can be increased without deterioration of quality by eliminating useless information form the original signal.

Citation Download Citation

Tu-Chih Tsai and Dimitris Anastassiou "Recursive Multi-Directional Image Filters", Proc. SPIE 0845, Visual Communications and Image Processing II, (13 October 1987); https://doi.org/10.1117/12.976501

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