Multi-focus Noisy Image Fusion using Low-Rank Representation

In the process of image acquisition, the noise is inevitable for source image. The multi-focus noisy image fusion is a very challenging task. However, there is no truly adaptive noisy image fusion approaches at present. As we all know, Low-Rank representation(LRR) is robust to noise and outliers. In this paper, we propose a novel fusion method based on LRR for multi-focus noisy image fusion. In the discrete wavelet transform(DWT) framework, the low frequency coefficients are fused by spatial frequency, the high frequency coefficients are fused by LRR coefficients and choose-max strategy. Finally, the fused image is obtained by inverse DWT. Experimental results demonstrate that the proposed algorithm can obtain state-of-the-art performance when the source images contain noise. The Code of our fusion method is available at https://github.com/hli1221/imagefusion_noisy_lrr