杂乱
计算机科学
假警报
红外线的
像素
人工智能
恒虚警率
对比度(视觉)
图像(数学)
差异(会计)
跟踪(教育)
可靠性(半导体)
图像增强
计算机视觉
模式识别(心理学)
光学
雷达
物理
电信
功率(物理)
会计
业务
心理学
教育学
量子力学
作者
Mahdi Nasiri,Saeed Chehresa
标识
DOI:10.1016/j.infrared.2017.03.003
摘要
In surveillance and early warning systems, the enhancement of targets is a very important stage for the high reliability detection and tracking in Infrared images with complex backgrounds. In order to enhance small targets in an Infrared image and suppress the background clutter, consequently increasing the contrast between them, this paper proposes a method using a model for the target area with a three-layer patch-image model and based on the difference between the variance of the layers in the neighboring areas of the investigated pixel. Results of the experiments indicate that the proposed method is quite effective on the enhancement of small targets as well as suppression of the background clutter in IR images with a minimum false alarm rate. This is realized while the runtime of the proposed method is minimal compared to other commonly used methods, which makes it effective to be used in real time applications.
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