Nonlinear model-based spatio-temporal filtering of image sequences
- 1 January 1991
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 2989-2992 vol.4
- https://doi.org/10.1109/icassp.1991.151031
Abstract
A Volterra model-based spatio-temporal filter for the enhancement of noise-corrupted image sequences is considered. This model uses estimates of higher-order statistics (HOS) to filter non-wide-sense stationary (WSS) image sequences that cannot be correctly modeled by second-order statistics alone. Some results are shown for this filter when it is applied along the direction of motion in image sequences with simulated noise.Keywords
This publication has 7 references indexed in Scilit:
- Image modeling using higher-order statistics with application to predictive image codingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Tutorial on higher-order statistics (spectra) in signal processing and system theory: theoretical results and some applicationsProceedings of the IEEE, 1991
- Signal detection and classification using matched filtering and higher order statisticsIEEE Transactions on Acoustics, Speech, and Signal Processing, 1990
- Geometrical properties of optimal Volterra filters for signal detectionIEEE Transactions on Information Theory, 1990
- Spatio-Temporal Motion Compensated Noise Filtering Of Image SequencesPublished by SPIE-Intl Soc Optical Eng ,1989
- Adaptive Linear Predictive Coding of Time-Varying Images Using Multidimensional Recursive Least Squares Ladder FiltersIEEE Journal on Selected Areas in Communications, 1987
- Adaptive Noise Smoothing Filter for Images with Signal-Dependent NoisePublished by Institute of Electrical and Electronics Engineers (IEEE) ,1985