Detail preserved fusion of visible and infrared images using regional saliency extraction and multi-scale image decomposition

By Guangmang Cui, Huajun Feng, Zhi-hai Xu, Qi Li, Yue-ting Chen. 2015

561 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Media Technology, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/3d04954f2bb32a1464ec391a566c173ad6c670ed

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Media Technology

1. Jinyuan Liu
2. Risheng Liu
3. Wei Zhong
4. Zhongxuan Luo
5. Long Ma
6. Qi Feng
7. Renhua Wang
8. Chang Li

Citations in the corpus

• Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and Segmentation (2023, background): “Four objec-tive metrics are leveraged for the comparison, including entropy (EN)[48], standard deviation (SD)[49], spatial frequency (SF)[50] and the sum of the correlations of differences (SCD)[51].”
• AttentionFGAN: Infrared and Visible Image Fusion Using Attention-Based Generative Adversarial Networks (2021, methodology): “The hybrid methods can combine the advantages of different methods, the example of those methods include multi-scale transform and sparse representation methods [22], saliency based and multi-scale transform methods [23].”