Open AccessBackground suppression of small target image based on fast local reverse entropy operator
Author(s) -
Deng He,
Wei Yantao,
Tong Mingwen
Publication year - 2013
Publication title -
iet computer vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 37
eISSN - 1751-9640
pISSN - 1751-9632
DOI - 10.1049/iet-cvi.2012.0240
Subject(s) - false alarm , entropy (arrow of time) , artificial intelligence , computer science , operator (biology) , pattern recognition (psychology) , computer vision , principle of maximum entropy , physics , biochemistry , chemistry , repressor , quantum mechanics , transcription factor , gene
Background suppression is vitally important for the small target detection, which aims to enhance targets and improve the signal‐to‐noise ratio of small target images. Consequently, the study proposes a background suppression approach based on the fast local reverse entropy operator, which is designed according to the fact that the appearance of a small target could result in the great change of the value of local reverse entropy in the local region. The operator is adopted to suppress complex backgrounds of small target images in order to enhance small targets, and then bring about high probabilities of detection and low probabilities of false alarm in the small target detection. Both quantitative and qualitative analyses contribute to confirm the validity and efficiency of the proposed approach.