SimpleFusion: A Simple Fusion Framework for Infrared and Visible Images

TL;DR

SimpleFusion is a straightforward and efficient framework for infrared and visible image fusion that decomposes images into reflectance and illumination components and fuses them using two plain CNNs, outperforming previous methods.

Contribution

It introduces a simple, flexible fusion framework based on Retinex theory with novel loss functions, avoiding complex architectures or pretrained models.

Findings

Outperforms previous state-of-the-art methods on benchmark datasets.

Efficient with two plain CNNs without downsampling.

Effectively preserves complementary information between modalities.

Abstract

Integrating visible and infrared images into one high-quality image, also known as visible and infrared image fusion, is a challenging yet critical task for many downstream vision tasks. Most existing works utilize pretrained deep neural networks or design sophisticated frameworks with strong priors for this task, which may be unsuitable or lack flexibility. This paper presents SimpleFusion, a simple yet effective framework for visible and infrared image fusion. Our framework follows the decompose-and-fusion paradigm, where the visible and the infrared images are decomposed into reflectance and illumination components via Retinex theory and followed by the fusion of these corresponding elements. The whole framework is designed with two plain convolutional neural networks without downsampling, which can perform image decomposition and fusion efficiently. Moreover, we introduce decomposition loss and a detail-to-semantic loss to preserve the complementary information between the two modalities for fusion. We conduct extensive experiments on the challenging benchmarks, verifying the superiority of our method over previous state-of-the-arts. Code is available at \href{https://github.com/hxwxss/SimpleFusion-A-Simple-Fusion-Framework-for-Infrared-and-Visible-Images}{https://github.com/hxwxss/SimpleFusion-A-Simple-Fusion-Framework-for-Infrared-and-Visible-Images}