A neighboring structure reconstructed matching algorithm based on LARK features

Aimed at the low contrast ratio and high noise of infrared images, and the randomness and ambient occlusion of its objects, this paper presents a neighboring structure reconstructed matching (NSRM) algorithm based on LARK features. The neighboring structure relationships of local window are considered based on a non-negative linear reconstruction method to build a neighboring structure relationship matrix. Then the LARK feature matrix and the NSRM matrix are processed separately to get two different similarity images. By fusing and analyzing the two similarity images, those infrared objects are detected and marked by the non-maximum suppression. The NSRM approach is extended to detect infrared objects with incompact structure. High performance is demonstrated on infrared body set, indicating a lower false detecting rate than conventional methods in complex natural scenes.