Bayesian methods for noise reduction in image processing

Details Bayesian methods for noise reduction in image processing Bayesian methods for noise reduction in image processing

2005-05-06

2010-10-12

Bhatnagar, Anand (Department: 2624)

Image analysis

Image enhancement or restoration

Image filter

C382S103000, C382S254000, C382S263000, C382S278000, C348S169000

Reexamination Certificate

active

07813581

ABSTRACT:
Improved methodology for image processing and object tracking that, inter alia, reduces noise. In one embodiment, the methodology is applied to moving targets, and comprises processing sequences of images that have been corrupted by one or more noise sources (e.g., sensor noise, medium noise, and/or target reflection noise). A likelihood or similar logical construct (e.g., Bayes' rule) is applied to the individual images (or aggregations thereof) of an image sequence in order to generate a posterior image for each observed image. The posterior images are fed-forward to the determination of the posterior image for one or more subsequent images (after smoothing), thereby making these subsequent determinations more accurate. The net result is a more accurate and noise-reduced representation (and location) of the target in each image.

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