Computationally efficient modeling of imagery using scaled, extracted principal components

a scaled, computationally efficient technology, applied in computing, instruments, electrical appliances, etc., can solve the problems of inability to handle voxels, fixed basis of jpeg and others cannot handle the expanded feature set associated with hyperspectral imagery, and standard compression has not been thought suitable for principal component image modeling and compression, etc., to reduce computation and the number of bits required, the effect of reducing the overhead of the computer

USRE42257E1Inactive Publication Date: 2011-03-29OL SECURITY LIABILITY CO
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Patent Information

Authority / Receiving Office
US · United States
Patent Type
Patents(United States)
Current Assignee / Owner
Publication Date
2011-03-29
Estimated Expiration
Not applicable · inactive patent

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Abstract

A computationally efficient modeling system for imagery scales both the original image and corresponding principal component tiles in the same proportion to be able to extract scaled principal components. The system includes recovery of feature weights for the image model by extracting the weights from the reduced size principal component tiles. The use of the reduced size tiles to derive weights dramatically reduces computer overhead both in the generation of the files and in the generation of the weights, and is made possible by the fact that the weights from the scaled down tiles are nearly equal to the weights of the tiles associated with the full size image. The subject system thus reduces computation and the number of bits required to represent features by first scaling the image and then tiling the image in the same proportion. In one embodiment, the scaled down tiles are used as training exemplars used to generate the principal components.
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Description

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims rights under U.S. Provisional Application Ser. No. 60 / 353,476, filed Mar. 31, 2002.

[0002] This application is a Reissue application of U.S. Ser. No. 10 / 334,816, filed Dec. 31, 2002, now U.S. Pat. No. 7,113,654, granted Sep. 26, 2006, which claims the benefit of Provisional Application No. 60 / 353,476, filed Jan. 31, 2002.STATEMENT OF GOVERNMENT INTEREST

[0003] This invention was made with U.S. Government support under Contract No. DAAL01-96-2-0002 with the Army Research Laboratory, and the U.S. Government has certain rights in the invention.FIELD OF INVENTION

[0004] This invention relates to image processing and more particularly to an efficient system for image modeling and compression.BACKGROUND OF THE INVENTION

[0005] The extraction of principal components from images is well known, with one extraction technique using neural networks as described in U.S. Pat. No. 5,377,305. Principal components are those which have self...

Examples

Embodiment Construction

[0029]Referring to FIG. 1, modeling and compression of an original image 10 is illustrated in which after the subject process is performed an approximation 12 of the original image is generated. The original image is divided up into 1−M segments with each of the segments being reflected in a different tile 14, with the tiled being shown as stacked. These tiles are of the same scale as the original image.

[0030]In order to extract principal components relating to features of the image, a transform 16 is applied to tiles 14 which results in a reduced set of tiles 18 referred herein as principal component feature tiles. These tiles are utilized to characterize features in the original image with the transform being one of a number of transforms which extract principal components. As mentioned hereinbefore U.S. Pat. No. 5,377,305 incorporated herein by reference and assigned to the assignee hereof describes a neural network technique for deriving principal components.

[0031]The principal ...