Sub-pixel detection for disparate target and background probability models

Alan Schaum

doi:10.1117/12.2616295

31 May 2022 Sub-pixel detection for disparate target and background probability models

Alan Schaum

Proceedings Volume 12094, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVIII; 120940P (2022) https://doi.org/10.1117/12.2616295
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

An accurate statistical model for detecting sub-pixel hyperspectral targets requires the convolution of probability functions for all possible mixture ratios. That computational difficulty has been avoided in the past by accepting one or more compromises to natural probability models for backgrounds and targets. This paper meets the convolution problem headon, finding solutions that represent good approximations for two conventional methods of composite hypothesis testing. The methodology produces a bonus, a generalization of the most popular method of hyperspectral background modeling.

Conference Presentation

Citation Download Citation

Alan Schaum "Sub-pixel detection for disparate target and background probability models", Proc. SPIE 12094, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVIII, 120940P (31 May 2022); https://doi.org/10.1117/12.2616295

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