Ming Chen^1,*, Guoqiang Ma², Ping Qi¹, Fucheng Wang¹, Lin Shen³, Xiaoya Pi¹

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.072623 - 10 February 2026

Abstract In the image fusion field, fusing infrared images (IRIs) and visible images (VIs) excelled is a key area. The differences between IRIs and VIs make it challenging to fuse both types into a high-quality image. Accordingly, efficiently combining the advantages of both images while overcoming their shortcomings is necessary. To handle this challenge, we developed an end-to-end IRI and VI fusion method based on frequency decomposition and enhancement. By applying concepts from frequency domain analysis, we used the layering mechanism to better capture the salient thermal targets from the IRIs and the rich textural information… More >

Mengke Tang¹, Yong Gan^2,*, Yifan Zhang¹, Xinxin Gan³

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2699-2716, 2025, DOI:10.32604/cmc.2025.064541 - 03 July 2025

Abstract Infrared imaging technology has been widely adopted in various fields, such as military reconnaissance, medical diagnosis, and security monitoring, due to its excellent ability to penetrate smoke and fog. However, the prevalent low resolution of infrared images severely limits the accurate interpretation of their contents. In addition, deploying super-resolution models on resource-constrained devices faces significant challenges. To address these issues, this study proposes a lightweight super-resolution network for infrared images based on an adaptive attention mechanism. The network’s dynamic weighting module automatically adjusts the weights of the attention and non-attention branch outputs based on the… More >

Can Wu^1,2, Wenyi Tang², Yunbo Rao^1,2,*, Yinjie Chen¹, Hui Ding², Shuzhen Zhu³, Yuanyuan Wang³

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1415-1434, 2025, DOI:10.32604/cmc.2025.059797 - 26 March 2025

Abstract Infrared unmanned aerial vehicle (UAV) target detection presents significant challenges due to the interplay between small targets and complex backgrounds. Traditional methods, while effective in controlled environments, often fail in scenarios involving long-range targets, high noise levels, or intricate backgrounds, highlighting the need for more robust approaches. To address these challenges, we propose a novel three-stage UAV segmentation framework that leverages uncertainty quantification to enhance target saliency. This framework incorporates a Bayesian convolutional neural network capable of generating both segmentation maps and probabilistic uncertainty maps. By utilizing uncertainty predictions, our method refines segmentation outcomes, achieving… More >

Junpeng Wu^1,2,*, Xingfan Jiang²

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 897-915, 2025, DOI:10.32604/cmc.2025.058714 - 26 March 2025

Abstract As technologies related to power equipment fault diagnosis and infrared temperature measurement continue to advance, the classification and identification of infrared temperature measurement images have become crucial in effective intelligent fault diagnosis of various electrical equipment. In response to the increasing demand for sufficient feature fusion in current real-time detection and low detection accuracy in existing networks for Substation fault diagnosis, we introduce an innovative method known as Gather and Distribution Mechanism-You Only Look Once (GD-YOLO). Firstly, a partial convolution group is designed based on different convolution kernels. We combine the partial convolution group with… More >

Song Qian, Guzailinuer Yiming, Ping Li, Junfei Yang, Yan Xue, Shuping Zhang^*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4069-4091, 2025, DOI:10.32604/cmc.2025.059931 - 06 March 2025

Abstract Infrared and visible light image fusion technology integrates feature information from two different modalities into a fused image to obtain more comprehensive information. However, in low-light scenarios, the illumination degradation of visible light images makes it difficult for existing fusion methods to extract texture detail information from the scene. At this time, relying solely on the target saliency information provided by infrared images is far from sufficient. To address this challenge, this paper proposes a lightweight infrared and visible light image fusion method based on low-light enhancement, named LLE-Fuse. The method is based on the… More >

Sanxia Shi, Yinglei Song^*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2911-2934, 2024, DOI:10.32604/cmc.2024.055363 - 18 November 2024

Abstract Infrared small target detection technology plays a pivotal role in critical military applications, including early warning systems and precision guidance for missiles and other defense mechanisms. Nevertheless, existing traditional methods face several significant challenges, including low background suppression ability, low detection rates, and high false alarm rates when identifying infrared small targets in complex environments. This paper proposes a novel infrared small target detection method based on a transformed Gaussian filter kernel and clustering approach. The method provides improved background suppression and detection accuracy compared to traditional techniques while maintaining simplicity and lower computational costs.… More >

Shuang Kang¹, Yinchao He^1,2, Wenwen Li^1,*, Sen Liu²

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 933-949, 2024, DOI:10.32604/cmc.2024.056614 - 15 October 2024

Abstract To address the issues of low accuracy and high false positive rate in traditional Otsu algorithm for defect detection on infrared images of wind turbine blades (WTB), this paper proposes a technique that combines morphological image enhancement with an improved Otsu algorithm. First, mathematical morphology’s differential multi-scale white and black top-hat operations are applied to enhance the image. The algorithm employs entropy as the objective function to guide the iteration process of image enhancement, selecting appropriate structural element scales to execute differential multi-scale white and black top-hat transformations, effectively enhancing the detail features of defect… More >

Chunming Wu¹, Wukai Liu^2,*, Xin Ma³

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1441-1461, 2024, DOI:10.32604/cmc.2024.048136 - 25 April 2024

Abstract A novel image fusion network framework with an autonomous encoder and decoder is suggested to increase the visual impression of fused images by improving the quality of infrared and visible light picture fusion. The network comprises an encoder module, fusion layer, decoder module, and edge improvement module. The encoder module utilizes an enhanced Inception module for shallow feature extraction, then combines Res2Net and Transformer to achieve deep-level co-extraction of local and global features from the original picture. An edge enhancement module (EEM) is created to extract significant edge features. A modal maximum difference fusion strategy More >

Xiao Luo^1,3, Hao Zhu^1,2,*, Zhenli Zhang^1,2

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2667-2687, 2024, DOI:10.32604/cmc.2024.047988 - 27 February 2024

Abstract Road traffic safety can decrease when drivers drive in a low-visibility environment. The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of accidents. To tackle the challenges posed by the low recognition accuracy and the substantial computational burden associated with current infrared pedestrian-vehicle detection methods, an infrared pedestrian-vehicle detection method A proposal is presented, based on an enhanced version of You Only Look Once version 5 (YOLOv5). First, A head specifically designed for detecting small targets has been integrated into… More >

Naglaa F. Soliman^1,2, E. A. Alabdulkreem³, Abeer D. Algarni^1,*, Ghada M. El Banby⁴, Fathi E. Abd El-Samie^1,5, Ahmed Sedik⁶

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2545-2563, 2022, DOI:10.32604/cmc.2022.020107 - 29 March 2022

Abstract For military warfare purposes, it is necessary to identify the type of a certain weapon through video stream tracking based on infrared (IR) video frames. Computer vision is a visual search trend that is used to identify objects in images or video frames. For military applications, drones take a main role in surveillance tasks, but they cannot be confident for long-time missions. So, there is a need for such a system, which provides a continuous surveillance task to support the drone mission. Such a system can be called a Hybrid Surveillance System (HSS). This system… More >