Hierarchical Feature Enhancement Algorithm for Multispectral Infrared Images of Dark and Weak Targets

Abstract

A multispectral infrared zoom optical system design and a single-frame hierarchical guided filtering image enhancement algorithm are proposed to address the technical problems of low contrast, blurred edges, and weak signal strength of single-spectrum infrared imaging of faint targets, which are easily drowned out by noise. The multispectral infrared zoom optical system, based on the theory of complex achromatic and mechanical positive group compensation, can simultaneously acquire multispectral image information for faint targets. The single-frame hierarchical guided filtering image enhancement algorithm, which extracts the background features and detailed features of faint targets in a hierarchical manner and then weights fusion, effectively enhances the target and suppresses the interference of complex background and noise. Solving multi-frame processing increases data storage and real-time challenges. The experimental verification of the optical system design and image enhancement algorithm proposed in this paper separately verified that the experimental enhancement was significant, with the combined use improving Mean Square Error (MSE) by 14.32, Signal-Noise Ratio (SNR) by 11.64, Peak Signal-to-Noise Ratio (PSNR) by 12.78, and Structural Similarity (SSIM) by 14.0% compared to guided filtering. This research lays the theoretical foundation for the research of infrared detection and tracking technology for clusters of faint targets.