Small target detection based on weighted self-information map

• Published in: Infrared physics & technology 2013-09, Vol.60, p.197-206
• Main Authors: Deng, He, Wei, Yantao, Tong, Mingwen
• Format: Article
• Language: English
• Subjects: Background suppression; Construction; False alarms; Infrared; Mathematical analysis; Nonuniformity; Parzen window; Quantitative analysis; Self-information map; Signal to noise ratio; Small target detection; Target detection; Threshold segmentation
• ISSN: 1350-4495; 1879-0275
• DOI: 10.1016/j.infrared.2013.05.003

•A weighted self-information map is proposed to overcome the target growing effect.•The seed point and stopping criterion are selected automatically in the improving region growing technique.•The presented approach yields high detection probability and low false alarm probability. The target growing effect and large calculation are two major drawbacks in small target detection based on the self-information map. Consequently, a weighted self-information map is proposed to overcome those disadvantages in this paper. The removal of the target growing effect from the weighted self-information map is proved theoretically, which is capable of improving the capability of small target detection. Based on the weighted self-information map and the improved region growing technology, a small-target detection approach is constructed. The signal-to-noise ratio, peak signal-to-noise ratio, region nonuniformity, the probability of detection and the probability of false alarm are adopted to demonstrate the performance of the proposed approach. Both quantitative analysis and qualitative comparison confirm the validity and efficiency of the proposed approach.