RX infrared small target detection algorithm based on multi-scale local strength and gradient fusion

Jing Tian, D. Song, Yingguang Hao, Weiwei Yin, Rui Li, Ke Han
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引用次数: 0

Abstract

Infrared small target detection under complex background is still a challenging computer vision task. An image usually contains complex background, weak targets and chaotic noise. In order to solve this problem, we must try our best to enhance the target signal to noise ratio (SNR) while suppressing the complex background factors. We proposed an RX infrared small target detection algorithm by analyzing multi-scale local gradient and local intensity fusion feature. According to the gradient points to the target center and the intensity value of the target pixel is greater than the intensity value of its local adjacent pixels, We used multi-scale information to calculate the local gradient map and local intensity map of infrared image and used RX global detection method to extract small targets. The experiment shows, our algorithm has good performance on detection result. It has good robustness and effectiveness, which can be applied to infrared small target detection under complex background.
基于多尺度局部强度和梯度融合的RX红外小目标检测算法
复杂背景下的红外小目标检测仍然是一项具有挑战性的计算机视觉任务。图像通常包含复杂的背景、弱目标和混沌噪声。为了解决这一问题,必须在抑制复杂背景因素的同时,尽力提高目标信噪比。提出了一种基于多尺度局部梯度和局部强度融合特征的RX红外小目标检测算法。根据梯度点指向目标中心以及目标像素的强度值大于其局部相邻像素的强度值,利用多尺度信息计算红外图像的局部梯度图和局部强度图,并利用RX全局检测方法提取小目标。实验表明,该算法在检测结果上具有良好的性能。该方法具有良好的鲁棒性和有效性,可应用于复杂背景下的红外小目标检测。
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