Infrared and Visible Image Fusion with ResNet and zero-phase component analysis

06/19/2018
by   Hui Li, et al.
2

In image fusion task, feature extraction and processing are keys for fusion algorithm. Not only traditional feature extraction methods, deep learning-based methods are also applied into image fusion field to extract features. However, most of them use deep features directly which without feature processing. And this will lead the fusion performance degradation in some cases. In this paper, a novel fusion framework which based on deep features and zero-phase component analysis(ZCA) is proposed. Firstly, the residual network(ResNet) is used to extract the deep features from source images. Then ZCA and l_1-norm are utilized to normalize the deep features and obtain initial weight maps. And the final weight maps are obtained by initial weight maps and soft-max operation. Finally, the fused image is reconstructed by weight maps and source images. Compare with the existing fusion methods, experimental results demonstrate that our algorithm achieves better performance in both objective assessment and visual quality. And the code of our fusion algorithm is available at https://github.com/exceptionLi/imagefusion_resnet50

READ FULL TEXT

page 5

page 7

page 11

page 12

research
04/19/2018

Infrared and Visible Image Fusion using a Deep Learning Framework

In recent years, deep learning has become a very active research tool wh...
research
11/06/2018

Infrared and visible image fusion using a novel deep decomposition method

Infrared and visible image fusion is an important problem in image fusio...
research
02/21/2021

A Deep Decomposition Network for Image Processing: A Case Study for Visible and Infrared Image Fusion

Image decomposition is a crucial subject in the field of image processin...
research
08/12/2022

SFF-DA: Sptialtemporal Feature Fusion for Detecting Anxiety Nonintrusively

Early detection of anxiety disorders is essential to reduce the sufferin...
research
09/14/2023

A Novel Local-Global Feature Fusion Framework for Body-weight Exercise Recognition with Pressure Mapping Sensors

We present a novel local-global feature fusion framework for body-weight...
research
04/25/2022

SwinFuse: A Residual Swin Transformer Fusion Network for Infrared and Visible Images

The existing deep learning fusion methods mainly concentrate on the conv...

Please sign up or login with your details

Forgot password? Click here to reset