Low-Contrast Infrared Target Detection Based on Multiscale Dual Morphological Reconstruction
Yongsong Li, Zhengzhou Li, Bitong Xu, Chujia Dang, Jiaqi Deng
Abstract
This letter proposes a novel method based on multiscale dual morphological reconstruction (MDMR) to detect low-contrast ship target with unknown size and polarity (bright or dark) in infrared image. First, the multiscale morphological reconstruction perceives the structural information of various scales. The target signal map (TSM) is presented to indicate the target polarity and enhance target by background subtraction and logarithmic histogram transform. Next, the boundary constraint entropy threshold selection (BCETS) is designed to extract candidate targets and avoid the over- or under-segmentation problems. Then, the local contour contrast descriptor (LCCD) is constructed and the discriminant rule of low-contrast target is established to identify true target and eliminate false alarms. Finally, the pixel-OR operation fuses the multiscale detection results. Extensive experiments show that the proposed method has a better effectiveness and robustness against compared methods.