Analysis of selection of structural element in mathematical morphology with application to infrared point target detection

Jiefeng Guo; Guilin Chen

doi:10.1117/12.754627

8 January 2008 Analysis of selection of structural element in mathematical morphology with application to infrared point target detection

Jiefeng Guo, Guilin Chen

Author Affiliations +

Proceedings Volume 6835, Infrared Materials, Devices, and Applications; 68350P (2008) https://doi.org/10.1117/12.754627
Event: Photonics Asia 2007, 2007, Beijing, China

Abstract

Low signal-to-noise ratio and complex background make the point target detection from infrared image a challenging and difficult problem. Combining the filtering characteristic of opening operation of mathematical morphology and the technique of background prediction, this paper presents a point target detection algorithm based on mathematical morphology, including analytic expressions for the detection algorithm. The selection of structural element is the key of mathematical morphology. The analyzing method of selection of structural element is presented. This paper mainly analyzes and compares the different performances produced by four kinds of structural elements having different size and shape, when these structural elements process the different components of complex background and point target. The analyzing and comparing methods focus on the curves generated by plotting the samples of image in row in which the point target exists. This analyzing method of selection of structural element is effective. The experiment results of detection algorithm using four kinds of structural elements to respectively process the infrared point target image are also presented and analyzed, including the probability of detection and the number of false targets.

Citation Download Citation

Jiefeng Guo and Guilin Chen "Analysis of selection of structural element in mathematical morphology with application to infrared point target detection", Proc. SPIE 6835, Infrared Materials, Devices, and Applications, 68350P (8 January 2008); https://doi.org/10.1117/12.754627

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