IEEE Transactions on Geoscience and Remote Sensing· 2013Q1
A Local Contrast Method for Small Infrared Target Detection
- 1,287citations
- Q1SCImago
- 2013year
Short summary
A novel local contrast measure enhances small infrared targets by quantifying dissimilarity between a pixel and its surroundings, simultaneously boosting target signal and suppressing background clutter.
AI-generated from the title and abstract; the full text is not read.
Key points
- A local contrast measure quantifies pixel dissimilarity to its neighborhoods for target enhancement.
- The method simultaneously achieves target signal enhancement and background clutter suppression.
- An adaptive threshold is used in the second stage for target segmentation.
- Experimental results validate the algorithm's detection capability, simplicity, and effectiveness in improving SNR.
AI-generated from the title and abstract; the full text is not read.
Abstract
Robust small target detection of low signal-to-noise ratio (SNR) is very important in infrared search and track applications for self-defense or attacks. Consequently, an effective small target detection algorithm inspired by the contrast mechanism of human vision system and derived kernel model is presented in this paper. At the first stage, the local contrast map of the input image is obtained using the proposed local contrast measure which measures the dissimilarity between the current location and its neighborhoods. In this way, target signal enhancement and background clutter suppression are achieved simultaneously. At the second stage, an adaptive threshold is adopted to segment the target. The experiments on two sequences have validated the detection capability of the proposed target detection method. Experimental evaluation results show that our method is simple and effective with respect to detection accuracy. In particular, the proposed method can improve the SNR of the image significantly.
The authors' abstract, as published at the source. IEEE Transactions on Geoscience and Remote Sensing, 2013 · DOI ↗
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Field: Aerospace Engineering
Aerospace EngineeringEngineering