Feature Preservation and Shape Cues Assist Infrared Small Target Detection

Abstract

Infrared small target detection (ISTD) aims to segment small target pixels from infrared images and has extensive applications in many fields. Despite multiple progress, challenges remain as present methods still easily suffer from missed detection. Also, present methods are not sensitive enough to irregular target shapes. We argue that the main reason is that some informative small target features get lost during the aggressive downsampling in the encoder without effective recovery. In this article, we propose a new network with a dual-branch encoder-decoder structure for ISTD to address the two challenges. Specifically, to better preserve small target body features for more accurate target locations, we propose to maintain a relatively high resolution of feature maps in one encoder branch. For the other encoder branch, we gradually enlarge feature channels while shrinking resolutions and devise Perona-Malik diffusion (PMD) blocks to preserve shape cues inspired by the shape-preserving effect of PMD in denoising. The encoded high-resolution target body features and high-channel shape cues actually complement each other, so we design channel-resolution interact modules (CRIMs) to combine them. In the decoder, we propose orthogonal central difference fusion (OCDF) that relies on mining contrast differences to further refine shape-aware ISTD quality. Experiments on NUAA-SIRST and IRSTD-1k prove the superiority of our method.