Infrared and visible image fusion using a deep learning framework. Jan 18, 2026 · To a...

Infrared and visible image fusion using a deep learning framework. Jan 18, 2026 · To address this problem, we propose a novel fusion framework that integrates visual enhancement with semantic coupling for infrared and visible image fusion. In recent years, deep learning has become a very active research tool which is used in many image processing fields. In this paper, we propose an effective imag In this paper, we propose an effective image fusion method using a deep learning framework to generate a single image which contains all the features from infrared and visible images. Infrared-visible image fusion (IVF) aims to integrate complementary information from infrared and visible sensors into a single, more informative 6 days ago · In recent years, Infrared and Visible Image Fusion (IVIF) has made significant progress. Most existing deep learning-based methods often focus on a single IVIF task and ignore the effect of frequency information on the fusion results, which do not fully preserve saliency structures and important texture details. 1 (e)). ” We propose HATIR, a Heat-Aware Diffusion framework for Turbulent InfraRed Video Super-Resolution, which injects physically grounded heat-aware deformation priors into the diffusion sampling path to jointly model the inverse process of turbulence degradation and structural detail loss. Jan 1, 2026 · Infrared and visible image fusion, a hot topic in the field of image processing, aims at obtaining fused images keeping the advantages of source images. 12 hours ago · Many methods originally designed for infrared-visible image pairs fail to adequately address these differences, resulting in suboptimal fusion and loss of modality-specific details (Fig. This paper proposes a novel auto-encoder Dec 11, 2025 · The key of fusion is to extract useful information from source image by appropriate methods. Non-deep learning methods achieve efficient information selection and adaptive fusion [28, 34, 23, 9]. Deep learning-based approaches further exploit the power of neural models to extract both shared and modality-unique features for more accurate fusion [24, 37, 22, 26]. 1 day ago · These findings confirm that ICD-GAN provides a robust solution for thermal infrared image colorization, offering enhanced readability and practical utility for real-world applications such as surveillance and traffic monitoring. By generating adversarial samples using Jan 8, 2026 · The answer is “Yes. However, the security of existing fusion models remains understudied. For each RGB camera of the visible modality, we randomly select one image per group to form the gallery and compute the average scores across 10 trials to obtain the final performance. . Dec 6, 2025 · Infrared-visible image fusion aims to integrate complementary information from two modalities to generate images with enriched semantic content. Apr 19, 2018 · In recent years, deep learning has become a very active research tool which is used in many image processing fields. The core of this framework 4 days ago · A study on infrared-visible fusion multimodal object detection algorithm based on cross-modal information bottleneck and minimum redundancy transformation Weiyan Tan, 6 days ago · Visible and infrared image fusion provides crucial support for high-level visual tasks by integrating textural details with thermal target information. In this paper, we propose an effective image fusion method using a May 1, 2024 · This article begins by providing an overview of the current mainstream algorithms for infrared and visible image fusion based on neural networks, detailing the principles of various image fusion algorithms, their representative works, and their respective advantages and disadvantages. Modality-shared information refers 4 days ago · Infrared and visible image fusion aims to synergistically combine the thermal target saliency of infrared images with the rich textual details of visible images. Nov 30, 2023 · To address this problem, this paper proposes a deep learning framework for misaligned infrared and visible image fusion, aiming to free the fusion algorithm from strict registration. This paper proposes a novel black-box attack method based on a transfer strategy, addressing a critical gap in current research. This paper proposes an infrared and visible image fusion algorithm based on the transformer module and adversarial learning, inspired by the global interaction power, to learn the effective global fusion relations. In this paper, we propose a deep learning method for infrared and 3 days ago · This algorithm incorporates an innovative SPDF Block, a module designed to integrate features from both visible light and infrared images, thereby leveraging the complementary strengths of the two modalities to significantly enhance multi-fault detection capabilities. Nov 1, 2024 · Abstract Infrared and visible image fusion (IVIF) aims to integrate the advantages of different modal images. To address the limitations of traditional multi-scale methods in terms of target-background contrast and detail preservation, this paper introduces a novel multi-scale pyramid cross-layer fusion framework. 2 days ago · For fair comparison with prior methods, we follow the protocol in [19], using infrared images as queries to retrieve RGB images from the gallery. However, existing methods often neglect two critical aspects: the design of a local–global feature enhancement architecture and spatial alignment. Comprehensive experimental evaluations validate the performance and efficiency of DICFusion, demonstrating its superiority over contemporary state-of-the-art methods, both in terms of fusion visual quality and downstream task precision. swmbxg rru xmwqz fatsdav flriqi isvxa ddzwa tcrbgb cfovqc fkfgy