Image-enhanced estimation methods
Article Abstract:
Advances in online image processing make possible significant improvements in estimation algorithm performance. Raw image data is received by sophisticated processors as a sequence of matrices of gray levels generated in packets or frames at a fixed frame rate. The processor recasts the data and extracts relevant features from it, acting as both a data compression and focusing element. The processor also serves as a pattern classifier that places images in prespecified sets of topical bins, which reduces the output data rate to a manageable level. Errors occurring in the image link are distinct from those in the conventional observation links. The algorithms presented here are similar to single-model algorithms, but they assume that image augmentation is exploited rather than using center-of-reflection measurements exclusively.
Publication Name: Proceedings of the IEEE
Subject: Electronics
ISSN: 0018-9219
Year: 1993
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Order statistics in digital image processing
Article Abstract:
New techniques for nonlinear image processing are used in digital image filtering, image enhancement, and edge detection. Nonlinear image filters based on order statistics are robust in the presence of impulsive noise and tend to preserve edge information, which is important for human perception. They are relatively easy and fast to compute, compared to linear filters, all of which makes them popular for image processing applications. However, they are relatively difficult to analyze theoretically compared to linear filter analysis. New tools have been developed recently to facilitate nonlinear image filter analysis. The properties of nonlinear image filters and their algorithmic computation are presented.
Publication Name: Proceedings of the IEEE
Subject: Electronics
ISSN: 0018-9219
Year: 1992
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Image understanding environments
Article Abstract:
Image understanding (IU) software environments enable the conversion of object image data and object types into binary programming abstractions suitable for manipulation. Such environments consist of the underlying programming environment, types of objects, their programming constructs, system-specific object data bases and user interface. These functional aspects are detailed and compared in several IU systems. Trends in IU environments include lower cost, greater power and more common use, all driven by complementary trends in hardware, software and vision research and development.
Publication Name: Proceedings of the IEEE
Subject: Electronics
ISSN: 0018-9219
Year: 1988
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