基于轮廓波和稀疏表示的红外图像与SAR图像融合改进方法

Xiuxia Ji
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引用次数: 3

摘要

本文提出了一种改进的基于轮廓let变换和稀疏表示的红外图像与SAR图像融合方法。该方法通过轮廓let变换将源图像分解为低频子带系数和高频子带系数。对稀疏度较低的低频系数进行稀疏表示,构造全字典,在训练好的字典上求解稀疏系数,选择能量融合规则较大的低频系数。采用梯度极大值融合高频子带系数。利用不同的频率系数对融合后的图像进行反等高线let变换重建。实验结果表明,该方法在视觉质量和客观评价方面是一种可行有效的图像融合方法。
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An Improved Image Fusion Method of Infrared Image and SAR Image Based on Contourlet and Sparse Representation
In this paper, we propose an improved image fusion method of infrared image and SAR image based on the Contour let transform and sparse representation. For the method, it decompose the source image into the low frequency sub band coefficients and the high frequency sub band coefficients with the Contour let transform. The low frequency coefficients with lower sparseness are dealed with sparse representation, construct over complete dictionary, solve sparse coefficient over the trained dictionary, and choose the low frequency coefficients with the larger energy fusion rule. The high frequency sub band coefficients are fused by gradient maxim in. Different frequency coefficients are used to reconstruct the fused image by the inverse Contour let transform. Experimental results show that the proposed method is a feasible and effective image fusion method in term of visual quality and objective evaluation.
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