基于显著性的红外图像强固定模式噪声抑制*

本文针对红外成像设备对天远距离观测中得到的小目标、强固定模式噪声这一类典型数据提出基于显著性的红外图像强固定模式噪声抑制算法。文中首先对此类图像数据进行特性分析，指出图像中目标区域相对于背景固定模式噪声区域是显著的，利用显著性检测算法分离出图像中目标区域及背景，对不同区域分别采取不同处理，仅基于单幅图像信息实现强固定模式噪声的有效抑制。最后，通过大量小目标、强固定模式噪声红外图像对算法性能进行测试，结果表明，本算法能够准确提取出图像中目标区域，实现图像中强固定模式噪声的有效抑制。

Saliency based IR image heavy fixed pattern noise suppression

A saliency based heavy fixed pattern noise suppression algorithm for IR image which is captured by infrared focal-plane-array sensors in remote observation is proposed in this paper. We analyze the properties of the typical IR images characterized with small targets and heavy fixed pattern noise and point out that the target regions are more salient than the background for observer in IR image. Using the saliency detection algorithm to detect target regions, the proposed algorithm processes different regions separately and suppresses of the heavy fixed pattern noise effectively. Experiments indicate that our algorithm can detect the target regions accurately and suppress the heavy fixed pattern noise effectively.