Statistical analysis of infrared image sequences

Wilhelm Meier; Heinz-Dieter vom Stein

doi:10.1117/12.182864

17 August 1994 Statistical analysis of infrared image sequences

Wilhelm Meier, Heinz-Dieter vom Stein

Proceedings Volume 2357, ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision; (1994) https://doi.org/10.1117/12.182864
Event: Spatial Information from Digital Photogrammetry and Computer Vision: ISPRS Commission III Symposium, 1994, Munich, Germany

Abstract

This paper addresses the problem of focusing the attention of image processing steps to the relevant regions and structures in image sequences. This technique is especially useful in the presence of a high amount of noise and clutter, which is very often the situation in infrared image sequences. It helps to save computations and increases the reliability of segmentation/classification steps. For this purpose we propose a scene-independent hierarchical correlation analysis procedure. It uses a pyramidal image structure together with a top-down search strategy. Therefore it is capable to deal with moving, scaled, and deformed objects. The result is expressed as a feature vector for small image regions. Additionally, we present a segmentation technique based on the autocorrelation coefficient as a test statistic. We further extend this technique to cope with various other statistics and introduce a local variance quotient in image sequences to be used in a two sample Kolmogorov-Smirnov test.

Citation Download Citation

Wilhelm Meier and Heinz-Dieter vom Stein "Statistical analysis of infrared image sequences", Proc. SPIE 2357, ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision, (17 August 1994); https://doi.org/10.1117/12.182864

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KEYWORDS

Image segmentation

Image processing

Statistical analysis

Infrared imaging

Infrared radiation

Image analysis

Computer vision technology

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