Paper
6 October 1998 Fast efficient algorithms for 3x3 ranked filters using finite-state machines
Author Affiliations +
Proceedings Volume 3521, Machine Vision Systems for Inspection and Metrology VII; (1998) https://doi.org/10.1117/12.326970
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States
Abstract
Median filters and ranked filters of ranks other than median have often been proposed or used to remove image noise as well as for other reasons. These are nonlinear operations, and often have relative long execution times, making them unsatisfactory for many speed-critical industrial applications. This paper builds on the earlier work of Mahmoodi and Waltz to provide efficient implementations of 3 X 3 ranked filters of ranks 1 (minimum), 2, 3, 4, 5 (median), 6, 7, 8, and 9 (maximum). These implementations are based on a partial realization of the SKIPSM (Separated- Kernel Image Processing using finite-State Machines) paradigm. A full SKIPSM realization is not possible because, except for the filters of ranks 1 and 9, these operations are not separable. This paper shows that, in spite of this lack of separability, the finite-state machine aspect of SKIPSM can be used to advantage. The emphasis is on software implementations, but implementation is pipelined hardware have also been demonstrated. In addition, a fast `full- SKIPSM' implementation of a slightly different ranked filter, sometimes called the `separable median' filter, is presented. This filter guarantees that the output pixels are of rank 4, 5, or 6. For typical noise-reduction applications, it is difficult to find a convincing argument that this filter is inferior in any meaningful way to the true median filter.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Frederick M. Waltz, Ralf Hack, and Bruce G. Batchelor "Fast efficient algorithms for 3x3 ranked filters using finite-state machines", Proc. SPIE 3521, Machine Vision Systems for Inspection and Metrology VII, (6 October 1998); https://doi.org/10.1117/12.326970
Lens.org Logo
CITATIONS
Cited by 13 scholarly publications and 2 patents.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Digital filtering

Image filtering

Nonlinear filtering

Image processing

Remote sensing

Sun

Video

RELATED CONTENT


Back to Top