Spatial pattern classification for optical agricultural remote sensing

Chi-hsin Wu; Peter C. Doerschuk

doi:10.1117/12.186567

21 September 1994 Spatial pattern classification for optical agricultural remote sensing

Chi-hsin Wu, Peter C. Doerschuk

Proceedings Volume 2298, Applications of Digital Image Processing XVII; (1994) https://doi.org/10.1117/12.186567
Event: SPIE's 1994 International Symposium on Optics, Imaging, and Instrumentation, 1994, San Diego, CA, United States

Abstract

We describe a new method for computing approximations to the marginal probability mass function of the random variables in a Markov random field (MRF). When applied to the a posteriori MRF, this yields approximations to the conditional marginal probability mass function, which is the key quantity in a Bayesian classifier. We apply these ideas to an optical agricultural remote sensing problem where they outperform the pixel-by-pixel ML classifier by 38%.

Citation Download Citation

Chi-hsin Wu and Peter C. Doerschuk "Spatial pattern classification for optical agricultural remote sensing", Proc. SPIE 2298, Applications of Digital Image Processing XVII, (21 September 1994); https://doi.org/10.1117/12.186567

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