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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滤镜增强可见光图像的对比度

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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程序非常重要。图像融合在空间域或变换域中执行。在空间域中实现了基于加权平均的图像融合。使用此方法的融合图像是低对比度和模糊图像。变换域中融合图像的质量优于空间域中融合图像的质量。在变换域中执行基于标准离散小波变换(DWT)的融合,与基于加权平均的融合相比,它产生更好的结果。但是,使用基于DWT的融合的融合图像缺少空间细节。在本文中,提出了一种简单的图像融合方法,以使用可见光图像的加权平均或基于DWT的图像融合技术来提高融合图像的质量。实际上,红外图像是模糊图像,因此在输入的红外图像和建议的锐化滤镜之间执行卷积处理。输出是具有突出边缘和精细细节的图像。使用加权平均或基于DWT的图像融合来融合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,所提出的融合方法比标准融合方法具有更好的效果。

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