使用图像融合和锐化过滤器增强可见红外图像的对比度

N. Habeeb, Salman Hussien Omran, Dahir Abbas Radih
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引用次数: 8

摘要

利用图像融合进行图像增强在许多应用中都是非常重要的。图像融合可在空间域或变换域进行。在空间域实现了基于加权平均的图像融合。采用这种方法融合的图像是低对比度和模糊图像。变换域的融合图像质量优于空间域的融合图像。在变换域进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,融合效果更好。然而,基于小波变换的融合图像缺乏空间细节。本文提出了一种简单的图像融合方法,利用加权平均或基于小波变换的可见红外图像融合来提高融合后图像的质量。红外图像本质上是一幅模糊图像,因此在输入的红外图像与所提出的锐化滤波器之间进行卷积处理。输出是一个突出显示边缘和精细细节的图像。利用加权平均或基于小波变换的图像融合,将可见光图像与增强后的红外图像进行融合,得到最终图像。实验结果表明,所提出的融合方法比标准的融合方法具有更好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Contrast Enhancement for Visible-Infrared Image Using Image Fusion and Sharpen Filters
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.
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