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Contrast Enhancement for Visible-Infrared Image Using Image Fusion and Sharpen Filters

机译:使用图像融合和锐化过滤器的可见红外图像对比增强

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Image enhancement using image fusion is very important for many applications. Image fusion is performed in spatial domain or in transform domain. Weighted averaging-based image fusion is achieved in spatial domain. The fused image using this method is a low-contrast and blurriness image. The quality of the fused image in transform domain is better than fused image in spatial domain. The standard Discrete Wavelet Transform (DWT) based fusion is performed in transform domain and it produces better result compared with the weighted averaging-based fusion. However, the fused image using DWT based fusion lacks spatial details. In this paper, a simple image fusion is proposed in order to enhance the quality of the fused image using weighted averaging or DWT based image fusion for visible-infrared images. In nature, infrared image is a blurred image, so the convolution process is performed between the input infrared image and the proposed sharpen filter. The output is an image with highlighting edges and fine details. Using weighted averaging or DWT based image fusion to fuse the visible image and the enhanced infrared image to obtain the final image. The experimental results showed that the proposed fusion method produces better results than the standard fusion methods.
机译:使用图像融合的图像增强对于许多应用非常重要。图像融合在空间域或转换域中执行。基于加权平均的图像融合在空间域中实现。使用此方法的熔融图像是低对比度和模糊图像。变换域中的熔融图像的质量优于空间域中的熔融图像。基于标准离散小波变换(DWT)的融合在变换域中进行,与基于加权平均的融合相比,它产生更好的结果。然而,使用基于DWT的融合的融合图像缺乏空间细节。在本文中,提出了一种简单的图像融合,以便使用加权平均或基于DWT的图像融合来增强融合图像的质量,用于可见红外图像。本质上,红外图像是模糊图像,因此在输入红外图像和所提出的锐化滤波器之间执行卷积处理。输出是具有突出显示边缘和精细细节的图像。使用加权平均或基于DWT的图像融合来熔化可见图像和增强的红外图像以获得最终图像。实验结果表明,该融合方法的融合方法优于标准融合方法。

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