Method of compressing hyperspectral images and detecting spectral anomalies

Andrey A. Zherebin; Leonid M. Tsibulkin; Tamara A. Tihomirova

doi:10.1117/12.454175

28 January 2002 Method of compressing hyperspectral images and detecting spectral anomalies

Andrey A. Zherebin, Leonid M. Tsibulkin, Tamara A. Tihomirova

Proceedings Volume 4541, Image and Signal Processing for Remote Sensing VII; (2002) https://doi.org/10.1117/12.454175
Event: International Symposium on Remote Sensing, 2001, Toulouse, France

Abstract

We present a method of image description based on sequential approximation. The spectrum of each pixel is represented as a sum of generalized reference spectra. At designing a new reference spectra the undescribed spectra components are modified using a predefined group of transformation in order to put them closer to each other. The reference spectrum is defined as a mean of modified spectra of pixels. The spectra poorly approximating by this scheme are assumed to be anomalous in respect to their surroundings. The pixels are eliminating from the process of reference spectrum's designing when the given accuracy of their spectrum's description is reached. We can interrupt the image coding at any time and translate the abnormal pixels distortionless, whereas the normal pixels would be described with predefined accuracy. If the main task is to detect and classify pixels with abnormal spectra, the 'normal' pixels can be translated roughly or ignored. This way we can compress the image without loss of information important for application.

Citation Download Citation

Andrey A. Zherebin, Leonid M. Tsibulkin, and Tamara A. Tihomirova "Method of compressing hyperspectral images and detecting spectral anomalies", Proc. SPIE 4541, Image and Signal Processing for Remote Sensing VII, (28 January 2002); https://doi.org/10.1117/12.454175

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