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The Election-pass Filtering and Image Fusion Algorithm Based on the Wavelet Transform for CW THz Image Processing

机译:基于小波变换的连续波太赫兹图像选择通滤波与图像融合算法

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The method of election-pass filtering and image fusion based on the wavelet transform is presented for eliminating the fringes in the continuous wave (CW) Terahertz (THz) Images. The CW THz images have the appearance of sinusoidal waves covering the image with standing wave patterns. The patterns result from reflected inside of the imaging system interfering with the images coming from the sample. The pattern interferes with contrast enhancement techniques, and can make the analysis of small areas difficult. An analysis is taken on the traditional method dealing with this problem by Frequency Domain Filtering and notch filtering, and the disadvantages of the traditional methods are shown. The Wavelet Transform is chosen to deal with the THz images and eliminate interference fringes. In the method, when the size of object is larger than one interference fringe, the character of the object can also be reserved. And the image fusion based on the Wavelet Transform is used to combine the background and the target with pixel-level fusion, which is proposed to improve the speed of identification and the quality of the fused image. Comparing the image restored via wavelet transform with other images, it can be found that the scope of continuous wave THz imaging's application can be extended and clearer images can be acquired.
机译:提出了一种基于小波变换的选通滤波和图像融合方法,以消除连续波(TW)太赫兹(THz)图像中的条纹。连续波太赫兹图像具有正弦波外观,并以驻波模式覆盖图像。这些图案是由于成像系统内部的反射干扰了来自样本的图像而产生的。该图案会干扰对比度增强技术,并可能使小区域分析变得困难。通过频域滤波和陷波滤波对传统方法进行了分析,指出了传统方法的弊端。选择小波变换来处理太赫兹图像并消除干扰条纹。在该方法中,当物体的尺寸大于一个干涉条纹时,也可以保留物体的特征。提出了一种基于小波变换的图像融合方法,将背景与目标结​​合在一起,并进行像素级融合,以提高识别速度和融合图像的质量。将通过小波变换恢复的图像与其他图像进行比较,可以发现连续波太赫兹成像的应用范围可以扩展,可以获得更清晰的图像。

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