Noise reduction filters for dynamic image sequences: a review
- 1 September 1995
- journal article
- review article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in Proceedings of the IEEE
- Vol. 83 (9) , 1272-1292
- https://doi.org/10.1109/5.406412
Abstract
In this paper, a thorough review is presented of noise reduction filters for digital image sequences. Detailed descriptions of several spatiotemporal and temporal noise reduction algorithms are provided. To aid in comparing between these different algorithms, we classify them based on their support (i.e., 3-D or 1-D filter) and whether or not motion compensation is employed. Several algorithms from each of the four categories are implemented and tested on real sequences degraded to various signal-to-noise ratios. These experimental results are discussed and analyzed to determine the overall advantages and disadvantages of the four general classifications, as well as, the individual filters.Keywords
This publication has 51 references indexed in Scilit:
- Bayesian restoration of image sequences using 3-D Markov random fieldsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Measurement of Image VelocityPublished by Springer Nature ,1992
- Noise reduction in heart movies by motion-compensated filteringPublished by SPIE-Intl Soc Optical Eng ,1991
- The estimation of velocity vector fields from time-varying image sequencesCVGIP: Image Understanding, 1991
- Least squares restoration of multichannel imagesIEEE Transactions on Signal Processing, 1991
- Nonstationary filtering of transmission tomograms in high photon counting noiseIEEE Transactions on Medical Imaging, 1991
- Temporally adaptive filtering of noisy image sequences using a robust motion estimation algorithmPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1991
- Digital restoration of multichannel imagesIEEE Transactions on Acoustics, Speech, and Signal Processing, 1989
- Image Estimation Using Doubly Stochastic Gaussian Random Field ModelsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1987
- Determining optical flowArtificial Intelligence, 1981