光学学报, 2020, 40 (2): 0210001, 网络出版: 2020-01-02   

基于Tikhonov正则化和细节重建的红外与可见光图像融合方法 下载: 1622次

Infrared and Visible Image Fusion Method Based on Tikhonov Regularization and Detail Reconstruction
作者单位
河海大学物联网工程学院, 江苏 常州 213022
摘要
传统的红外与可见光图像融方法将图像分解为多个频域分量后分别融合再相加,存在边缘模糊、对比度低等问题,为此提出了一种基于Tikhonov正则化和细节重建的融合方法。首先,利用Tikhonov正则化将图像分解为基本层和细节层,针对基本层训练一种用于细节重建的生成对抗网络;然后提取待融合图像的基本层特征,采用主成分分析方法进行融合;最后将基本层融合结果输入到生成对抗网络中,重建出一幅高频信息丰富的融合图像。实验结果表明:所提方法很好地保留了源图像中的细节信息和高亮区域,对不同清晰度的图像具有较好的鲁棒性。
Abstract
Traditional infrared and visible image fusion method decomposes images into several frequency components, fuses them separately, and then adds them together, resulting in problems of edge fuzziness, low contrast, and so on. The paper proposes a fusion method based on Tikhonov regularization and detail reconstruction. Firstly, images are decomposed into base layers and detail layers by Tikhonov regularization. A generative adversarial network is trained aiming at detail information reconstruction for base layers. Secondly, features of base layers to be fused are extracted, and the principal component analysis method is used for feature fusion. Finally, the fused results of base layers are input into generative network to reconstruct a fusion image with abundant high frequency information. Experimental results show that the method proposed in this paper preserves detail information and highlight areas of the source images well, with a good robustness to the images with different resolutions.

卢鑫, 杨林, 李敏, 张学武. 基于Tikhonov正则化和细节重建的红外与可见光图像融合方法[J]. 光学学报, 2020, 40(2): 0210001. Xin Lu, Lin Yang, Min Li, Xuewu Zhang. Infrared and Visible Image Fusion Method Based on Tikhonov Regularization and Detail Reconstruction[J]. Acta Optica Sinica, 2020, 40(2): 0210001.

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