Wei Yang, Liye Mei, Chuan Xu, Huan Zhang, Chuanwen Hu, Qianchuang Deng. Multi-Focus Image Fusion Method Based on Cooperative Detection via a Deep Dense Convolutional Neural Network[J]. Laser & Optoelectronics Progress, 2022, 59(24): 2410004
- Laser & Optoelectronics Progress
- Vol. 59, Issue 24, 2410004 (2022)
Fig. 1. Overall framework of proposed fusion method. (a) Collaborative detection via densely connected convolutional neural networks; (b) multi-scale information extraction for pyramid pooling network
Fig. 2. Structure of deep dense block
Fig. 3. Probabilistic decision diagram for multi-scale pyramid pooling collaborative detection. (a) Source image; (b) rough segmentation; (c) refined segmentation
Fig. 4. Lytro-3 image fusion results. A is corresponding fusion results obtained by various methods, and B is difference images in pseudo color map form obtained by subtracting source image A from each fused image
Fig. 5. Lytro-17 image fusion results. A is corresponding fusion results obtained by various methods, and B is difference images in pseudo color map form obtained by subtracting source image A from each fused image
Fig. 6. More results of proposed method. The first to fourth and fifth to eighth columns show fusion results of 18 pairs of multi-focus images, respectively
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Table 1. Comparison of objective evaluation of fusion results
| |||||||||||||||||||||||||||||||||||||||||||||||||||||
Table 2. Comparison of average objective evaluation of fusion results
Set citation alerts for the article
Please enter your email address
© Copyright 2018-2021 | Chinese Laser Press. All Rights Reserved 沪ICP备15018463号-20