Fast and Robust Small Infrared Target Detection Using Absolute Directional Mean Difference Algorithm
Infrared small target detection in an infrared search and track (IRST) system is a challenging task. This situation becomes more complicated when high gray-intensity structural backgrounds appear in the field of view (FoV) of the infrared seeker. While the majority of the infrared small target detection algorithms neglect directional information, in this paper, a directional approach is presented to suppress structural backgrounds and develop a more effective detection algorithm. To this end, a similar concept to the average absolute gray difference (AAGD) is utilized to construct a novel directional small target detection algorithm called absolute directional mean difference (ADMD). Also, an efficient implementation procedure is presented for the proposed algorithm. The proposed algorithm effectively enhances the target area and eliminates background clutter. Simulation results on real infrared images prove the significant effectiveness of the proposed algorithm.
Code (1)
Similar Papers 제목 키워드 기반
Filter design for small target detection on infrared imagery using normalized-cross-correlation layer
In this paper, we introduce a machine learning approach to the problem of infrared small target detection filter design. For this purpose, similarly to a convolutional layer of a neural network, the normalized-cross-corr…
SpirDet: Towards Efficient, Accurate and Lightweight Infrared Small Target Detector
In recent years, the detection of infrared small targets using deep learning methods has garnered substantial attention due to notable advancements. To improve the detection capability of small targets, these methods com…
DecoderThe First Competition on Resource-Limited Infrared Small Target Detection Challenge: Methods and Results
In this paper, we briefly summarize the first competition on resource-limited infrared small target detection (namely, LimitIRSTD). This competition has two tracks, including weakly-supervised infrared small target detec…
Small Aerial Target Detection for Airborne Infrared Detection Systems using LightGBM and Trajectory Constraints
Factors, such as rapid relative motion, clutter background, etc., make robust small aerial target detection for airborne infrared detection systems a challenge. Existing methods are facing difficulties when dealing with …
Binary ClassificationInfrared Small Target Detection based on Adjustable Sensitivity Strategy and Multi-Scale Fusion
Recently, deep learning-based single-frame infrared small target (SIRST) detection technology has made significant progress. However, existing infrared small target detection methods are often optimized for a fixed image…
Sensitivity