Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (44)
  • Open Access

    ARTICLE

    Retinexformer+: Retinex-Based Dual-Channel Transformer for Low-Light Image Enhancement

    Song Liu1,2, Hongying Zhang1,*, Xue Li1, Xi Yang1,3

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 1969-1984, 2025, DOI:10.32604/cmc.2024.057662 - 17 February 2025

    Abstract Enhancing low-light images with color distortion and uneven multi-light source distribution presents challenges. Most advanced methods for low-light image enhancement are based on the Retinex model using deep learning. Retinexformer introduces channel self-attention mechanisms in the IG-MSA. However, it fails to effectively capture long-range spatial dependencies, leaving room for improvement. Based on the Retinexformer deep learning framework, we designed the Retinexformer+ network. The “+” signifies our advancements in extracting long-range spatial dependencies. We introduced multi-scale dilated convolutions in illumination estimation to expand the receptive field. These convolutions effectively capture the weakening semantic dependency between pixels… More >

  • Open Access

    ARTICLE

    Secure Medical Image Retrieval Based on Multi-Attention Mechanism and Triplet Deep Hashing

    Shaozheng Zhang, Qiuyu Zhang*, Jiahui Tang, Ruihua Xu

    CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2137-2158, 2025, DOI:10.32604/cmc.2024.057269 - 17 February 2025

    Abstract Medical institutions frequently utilize cloud servers for storing digital medical imaging data, aiming to lower both storage expenses and computational expenses. Nevertheless, the reliability of cloud servers as third-party providers is not always guaranteed. To safeguard against the exposure and misuse of personal privacy information, and achieve secure and efficient retrieval, a secure medical image retrieval based on a multi-attention mechanism and triplet deep hashing is proposed in this paper (abbreviated as MATDH). Specifically, this method first utilizes the contrast-limited adaptive histogram equalization method applicable to color images to enhance chest X-ray images. Next, a… More >

  • Open Access

    ARTICLE

    Scene 3-D Reconstruction System in Scattering Medium

    Zhuoyifan Zhang1, Lu Zhang2, Liang Wang3, Haoming Wu2,*

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3405-3420, 2024, DOI:10.32604/cmc.2024.052144 - 15 August 2024

    Abstract Research on neural radiance fields for novel view synthesis has experienced explosive growth with the development of new models and extensions. The NeRF (Neural Radiance Fields) algorithm, suitable for underwater scenes or scattering media, is also evolving. Existing underwater 3D reconstruction systems still face challenges such as long training times and low rendering efficiency. This paper proposes an improved underwater 3D reconstruction system to achieve rapid and high-quality 3D reconstruction. First, we enhance underwater videos captured by a monocular camera to correct the image quality degradation caused by the physical properties of the water medium… More >

  • Open Access

    ARTICLE

    Improving the Transmission Security of Vein Images Using a Bezier Curve and Long Short-Term Memory

    Ahmed H. Alhadethi1,*, Ikram Smaoui2, Ahmed Fakhfakh3, Saad M. Darwish4

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4825-4844, 2024, DOI:10.32604/cmc.2024.047852 - 20 June 2024

    Abstract The act of transmitting photos via the Internet has become a routine and significant activity. Enhancing the security measures to safeguard these images from counterfeiting and modifications is a critical domain that can still be further enhanced. This study presents a system that employs a range of approaches and algorithms to ensure the security of transmitted venous images. The main goal of this work is to create a very effective system for compressing individual biometrics in order to improve the overall accuracy and security of digital photographs by means of image compression. This paper introduces… More >

  • Open Access

    ARTICLE

    RF-Net: Unsupervised Low-Light Image Enhancement Based on Retinex and Exposure Fusion

    Tian Ma, Chenhui Fu*, Jiayi Yang, Jiehui Zhang, Chuyang Shang

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1103-1122, 2023, DOI:10.32604/cmc.2023.042416 - 31 October 2023

    Abstract Low-light image enhancement methods have limitations in addressing issues such as color distortion, lack of vibrancy, and uneven light distribution and often require paired training data. To address these issues, we propose a two-stage unsupervised low-light image enhancement algorithm called Retinex and Exposure Fusion Network (RF-Net), which can overcome the problems of over-enhancement of the high dynamic range and under-enhancement of the low dynamic range in existing enhancement algorithms. This algorithm can better manage the challenges brought about by complex environments in real-world scenarios by training with unpaired low-light images and regular-light images. In the… More >

  • Open Access

    ARTICLE

    A Text Image Watermarking Algorithm Based on Image Enhancement

    Baowei Wang1,*, Luyao Shen2, Junhao Zhang2, Zenghui Xu2, Neng Wang2

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1183-1207, 2023, DOI:10.32604/cmc.2023.040307 - 31 October 2023

    Abstract Digital watermarking technology is adequate for copyright protection and content authentication. There needs to be more research on the watermarking algorithm after printing and scanning. Aiming at the problem that existing anti-print scanning text image watermarking algorithms cannot take into account the invisibility and robustness of the watermark, an anti-print scanning watermarking algorithm suitable for text images is proposed. This algorithm first performs a series of image enhancement preprocessing operations on the printed scanned image to eliminate the interference of incorrect bit information on watermark embedding and then uses a combination of Discrete Wavelet Transform More >

  • Open Access

    ARTICLE

    Underwater Waste Recognition and Localization Based on Improved YOLOv5

    Jinxing Niu1,*, Shaokui Gu1, Junmin Du2, Yongxing Hao1

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2015-2031, 2023, DOI:10.32604/cmc.2023.040489 - 30 August 2023

    Abstract With the continuous development of the economy and society, plastic pollution in rivers, lakes, oceans, and other bodies of water is increasingly severe, posing a serious challenge to underwater ecosystems. Effective cleaning up of underwater litter by robots relies on accurately identifying and locating the plastic waste. However, it often causes significant challenges such as noise interference, low contrast, and blurred textures in underwater optical images. A weighted fusion-based algorithm for enhancing the quality of underwater images is proposed, which combines weighted logarithmic transformations, adaptive gamma correction, improved multi-scale Retinex (MSR) algorithm, and the contrast… More >

  • Open Access

    ARTICLE

    Nondestructive Testing of Bridge Stay Cable Surface Defects Based on Computer Vision

    Fengyu Xu1,2, Masoud Kalantari3, Bangjian Li2, Xingsong Wang2,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2209-2226, 2023, DOI:10.32604/cmc.2023.027102 - 06 February 2023

    Abstract The automatically defect detection method using vision inspection is a promising direction. In this paper, an efficient defect detection method for detecting surface damage to cables on a cable-stayed bridge automatically is developed. A mechanism design method for the protective layer of cables of a bridge based on vision inspection and diameter measurement is proposed by combining computer vision and diameter measurement techniques. A detection system for the surface damages of cables is de-signed. Images of cable surfaces are then enhanced and subjected to threshold segmentation by utilizing the improved local grey contrast enhancement method More >

  • Open Access

    ARTICLE

    An Efficient Automated Technique for Classification of Breast Cancer Using Deep Ensemble Model

    Muhammad Zia Ur Rehman1, Jawad Ahmad2,*, Emad Sami Jaha3, Abdullah Marish Ali3, Mohammed A. Alzain4, Faisal Saeed5

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 897-911, 2023, DOI:10.32604/csse.2023.035382 - 20 January 2023

    Abstract Breast cancer is one of the leading cancers among women. It has the second-highest mortality rate in women after lung cancer. Timely detection, especially in the early stages, can help increase survival rates. However, manual diagnosis of breast cancer is a tedious and time-consuming process, and the accuracy of detection is reliant on the quality of the images and the radiologist’s experience. However, computer-aided medical diagnosis has recently shown promising results, leading to the need to develop an efficient system that can aid radiologists in diagnosing breast cancer in its early stages. The research presented… More >

  • Open Access

    ARTICLE

    Underwater Image Enhancement Using Customized CLAHE and Adaptive Color Correction

    Mousa Alhajlah*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5157-5172, 2023, DOI:10.32604/cmc.2023.033339 - 28 December 2022

    Abstract Underwater images degraded due to low contrast and visibility issues. Therefore, it is important to enhance the images and videos taken in the underwater environment before processing. Enhancement is a way to improve or increase image quality and to improve the contrast of degraded images. The original image or video which is captured through image processing devices needs to improve as there are various issues such as less light available, low resolution, and blurriness in underwater images caused by the normal camera. Various researchers have proposed different solutions to overcome these problems. Dark channel prior… More >

Displaying 21-30 on page 3 of 44. Per Page