Identification of mines in enhanced electro-optic images

Cheryl M. Smith; Susan M. Tuovila; Susan R. Nelson

doi:10.1117/12.324168

4 September 1998 Identification of mines in enhanced electro-optic images

Cheryl M. Smith, Susan M. Tuovila, Susan R. Nelson

Proceedings Volume 3392, Detection and Remediation Technologies for Mines and Minelike Targets III; (1998) https://doi.org/10.1117/12.324168
Event: Aerospace/Defense Sensing and Controls, 1998, Orlando, FL, United States

Abstract

Electro-optic (EO) sensors can be used for mine identification in turbid shallow water and very shallow water domains in which spatially- and temporally-variant conditions severely limit the effectiveness of acoustic and visual sensors. Also, EO sensors produce images with significantly finer resolution than acoustic sensors, making identification of mines possible rather than just classification of minelike targets. This paper presents image processing and enhancement techniques that improve mine identification probability. Due to the large variation in brightness, contrast, and texture across EO images, virtually all processing performed on these images must be local in nature. In an effort to compensate for the differences in image quality, several preprocessing techniques for noise reduction and contrast enhancement are applied to the images. A texture analysis is performed on the enhanced images in an effort to locate likely man-made surfaces. Of particular interest, the SUSAN (Smallest Univalue Segment Assimilating Nucleus) principle is investigated as a tool for both image enhancement and texture analysis. The performance of this technique, recently introduced by researchers from Oxford University, is compared with that of more traditional methods. The incompatibility of processes that produce visually appealing images with those that perform target detection is illustrated.

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Cheryl M. Smith, Susan M. Tuovila, and Susan R. Nelson "Identification of mines in enhanced electro-optic images", Proc. SPIE 3392, Detection and Remediation Technologies for Mines and Minelike Targets III, (4 September 1998); https://doi.org/10.1117/12.324168

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KEYWORDS

Image processing

Sensors

Electro optics

Mining

Visualization

Image enhancement

Naval mines

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