Paper
28 December 1979 Comparison Of Digital Image Filters And A Hybrid Smoother
H. A. Titus, J. L. Pereira
Author Affiliations +
Abstract
In the recent past considerable attention has been devoted to the application of Kalman filtering to smoothing out observation noise in image data. Optimal two-dimensional Kalman filtering algorithms require large amounts of storage and computation. Thus, the study of suboptimum estimators that require less computation is of importance. A comparison of some suboptimum image filters against the optimum non-recursive interpolator is accomplished. A new semi-causal (hybrid) filter is proposed that compensates the suboptimality of a simple two-dimensional recursive filter by means of an optimal combination of its estimate and a few non-causal observations.
© (1979) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
H. A. Titus and J. L. Pereira "Comparison Of Digital Image Filters And A Hybrid Smoother", Proc. SPIE 0207, Applications of Digital Image Processing III, (28 December 1979); https://doi.org/10.1117/12.958232
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Digital filtering

Image filtering

Digital image processing

Signal to noise ratio

Error analysis

Filtering (signal processing)

Electronic filtering

RELATED CONTENT

C Noise In Recursive Algorithms
Proceedings of SPIE (December 08 1978)
A Minimum-Error, Minimum-Correlation Filter For Images
Proceedings of SPIE (December 10 1986)
Efficient implementations of edge localization algorithms
Proceedings of SPIE (March 12 2002)
Kalman-filter-aided correlation for parameter estimation
Proceedings of SPIE (October 29 1997)

Back to Top