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Fuzzy SVM based pre-processing technique for infrared (IR) thermal images

机译:基于模糊的红外(IR)热图像预处理技术

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摘要

This paper proposes a noise removal algorithm to improve the quality of images captured by IR thermal cameras. Due to atmospheric disturbances and the temperature reflected from the surrounding objects, IR images are generally noisy. For removal of noise in IR thermal images the proposed algorithm has two stages. In the first stage, a support vector machine incorporated with fuzzy logic (FSVM) is used to obtain noise pixels from the thermal image and in the second stage an adaptive directional weighted median filter (ADWMF) is applied to restore noisy pixels. Our proposed algorithm is compared with another fuzzy-logic based noise classification technique, namely the adaptive fuzzy inference based directional median filter (AFIDMF). Simulation results indicate that the performance of the proposed filter is better, compared to AFIDMF based on the measures such as peak signal to noise ratio (PSNR) and structural similarity index (SSIM).
机译:本文提出了一种噪声去除算法,可以提高IR热敏摄像机捕获的图像质量。 由于大气干扰和从周围物体反射的温度,IR图像通常是嘈杂的。 为了在IR热图像中移除噪声,所提出的算法有两个阶段。 在第一阶段,与模糊逻辑(FSVM)的支持向量机用于从热图像中获得噪声像素,并且在第二阶段中应用自适应定向加权中值滤波器(ADWMF)以恢复噪声像素。 将所提出的算法与另一个基于模糊逻辑的噪声分类技术进行比较,即自适应模糊推断的方向中值滤波器(AFIDMF)。 仿真结果表明,基于诸如峰值信噪比(PSNR)和结构相似度指数(SSIM)的诸如峰值信号和结构相似度指数(SSIM)的措施,与AFIDMF相比,所提出的滤波器的性能更好。

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