Gauss-Markov-random-field-based small-target detection in infrared images

Wen Sheng; Jianguo Liu; Xingjian Wu

doi:10.1117/12.323679

25 September 1998 Gauss-Markov-random-field-based small-target detection in infrared images

Wen Sheng, Jianguo Liu, Xingjian Wu

Proceedings Volume 3545, International Symposium on Multispectral Image Processing (ISMIP'98); (1998) https://doi.org/10.1117/12.323679
Event: International Symposium on Multispectral Image Processing, 1998, Wuhan, China

Abstract

In this paper, a new small target detection approach which is based on the analysis of image background texture is presented, and Gaussian-Markov random field (GMRF) is chosen as texture model. Texture features can be obtained from the least square error estimation of GMRF parameters. Image is divided into non-overlapped blocks, and feature vector is obtained for each block. Using the normalized Euclidean distance of feature vectors as a measure of the difference of textures, target detection can be performed in a coarse to fine procedure according to the difference of features and approximation error.

Citation Download Citation

Wen Sheng, Jianguo Liu, and Xingjian Wu "Gauss-Markov-random-field-based small-target detection in infrared images", Proc. SPIE 3545, International Symposium on Multispectral Image Processing (ISMIP'98), (25 September 1998); https://doi.org/10.1117/12.323679

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