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

机译: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

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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.
机译:复杂背景下的红外小目标检测仍然是一个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。为了解决这个问题,我们必须尽力增强目标信号,同时抑制复杂的背景因素。我们通过分析多尺度局部梯度和局部强度融合功能来提出RX红外小目标检测算法。根据目标中心的梯度点和目标像素的强度值大于其本地相邻像素的强度值,我们使用了多尺度信息来计算红外图像的本地梯度图和局部强度映射并使用RX全球检测方法提取小目标。实验表明,我们的算法对检测结果具有良好的性能。它具有良好的稳健性和有效性,可在复杂背景下应用于红外小目标检测。

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