Image enhancement in multi-resolution multi-sensor fusion

J. Jang, Yong Sun Kim, J. Ra
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引用次数: 3

Abstract

In multi-sensor image fusion, multi-resolution approaches became popular because they can preserve detailed information well. Among them, the gradient-based multi-resolution (GBMR) algorithm is known to effectively reduce ringing artifacts near edges compared with the discrete wavelet transform (DWT)-based algorithm. However, since the GBMR algorithm does not consider the diagonal direction, the ringing artifacts reduction is not satisfactory at diagonal edges. In this paper, we generalize the GBMR algorithm by adopting the wavelet structure. Thereby, the proposed algorithm improves the fusion process in high-frequency sub-bands so as to preserve details of input images. Meanwhile, the algorithm fuses the low-frequency sub-band by considering the overall contrast in the output image. To evaluate the proposed algorithm, we compare it with the DWT-based and GBMR algorithms. Experimental results clearly demonstrate that the proposed algorithm effectively reduces ringing artifacts for edges of all directions and greatly enhances the overall contrast while minimizing visual information loss.
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多分辨率多传感器融合中的图像增强
在多传感器图像融合中,多分辨率方法因其能很好地保留细节信息而受到青睐。其中,基于梯度的多分辨率(GBMR)算法与基于离散小波变换(DWT)的算法相比,可以有效地减少边缘附近的环形伪影。然而,由于GBMR算法没有考虑对角方向,因此对角边缘处的环形伪影抑制效果不理想。本文采用小波结构对GBMR算法进行了推广。因此,该算法改进了高频子带的融合过程,以保持输入图像的细节。同时,考虑输出图像的整体对比度,对低频子带进行融合。为了评估该算法,我们将其与基于dwt和GBMR的算法进行了比较。实验结果清楚地表明,该算法有效地减少了各个方向边缘的环形伪影,大大提高了整体对比度,同时最大限度地减少了视觉信息损失。
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