Article
Optics
Weitao Deng, Lei Liu, Huateng Chen, Xiaofeng Bai
Summary: This paper proposes a contrast enhancement method based on adaptive histogram correction and equalization to effectively reduce artifacts and insufficient local detail enhancement caused by traditional methods.
Article
Computer Science, Information Systems
Abhash Kumar, Ashish Kumar Bhandari, Reman Kumar
Summary: This paper proposes a novel method for enhancing image contrast while retaining naturalness, using compensated histogram equalization and blending with an adaptive brightness adjustment kernel. The method is applicable to contrast degraded images and performs better than existing methods on the CSIQ dataset.
MULTIMEDIA SYSTEMS
(2021)
Article
Computer Science, Information Systems
Sanjay Agrawal, Rutuparna Panda, P. K. Mishro, Ajith Abraham
Summary: A novel joint histogram equalization (JHE) based technique is proposed in this research to improve the contrast of an image by utilizing the information among each pixel and its neighbors. The experimental analysis shows that this method outperforms the state-of-the-art histogram equalization algorithms in contrast enhancement, even for images with a narrow dynamic range.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Xin Fan, Junyan Wang, Haifeng Wang, Changgao Xia
Summary: A histogram-constrained and contrast-tunable HE technique for digital image enhancement is proposed in this paper, which partitions the input image histogram into two parts and redistributes them to achieve more accurate results in terms of information entropy and MS-SSIM compared to other algorithms.
Article
Computer Science, Information Systems
Zixuan Bian, Heng Yao, Yanfen Le, Chuan Qin
Summary: This paper proposes an RDH-CE algorithm that focuses on maintaining high image quality by guiding and controlling peak selection and histogram shift direction through quality metrics.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2023)
Article
Multidisciplinary Sciences
Xiaowen Zhang, Yongfeng Ren, Guoyong Zhen, Yanhu Shan, Chengqun Chu
Summary: In this paper, the image enhancement problem is treated as an optimization problem, and the particle swarm algorithm is used to find the optimal solution. An improved particle swarm optimization algorithm is proposed, which utilizes individual optimization, local optimization, and global optimization to adjust the particle's flight direction. The color image channels are represented by a quaternion matrix, and the proposed algorithm is used to optimize the transformation parameters.
Article
Multidisciplinary Sciences
Xiwen Liang, Xiaoyan Chen, Keying Ren, Xia Miao, Zhihui Chen, Yutao Jin
Summary: In this work, the authors propose a novel Adaptive Frequency Decomposition Network (AFDNet) for enhancing low-light images. They utilize an Adaptive Frequency Decomposition (AFD) module to extract low and high frequency information and improve contrast, noise, and detail. Extensive experiments show that AFDNet outperforms existing state-of-the-art methods both quantitatively and visually.
SCIENTIFIC REPORTS
(2023)
Article
Engineering, Electrical & Electronic
Yan Chai Hum, Yee Kai Tee, Wun-She Yap, Hamam Mokayed, Tian Swee Tan, Maheza Irna Mohamad Salim, Khin Wee Lai
Summary: This study proposes a novel pixel-based contrast enhancement algorithm based on human visual perception, which limits the enhancement of well-contrasted regions and enhances regions with poor contrast. Experimental results show that the algorithm consistently enhances images across different types.
SIGNAL PROCESSING-IMAGE COMMUNICATION
(2022)
Article
Computer Science, Information Systems
Diana Nunez-Ramirez, David Mata-Mendoza, Manuel Cedillo-Hernandez
Summary: In this paper, an improved preprocessing stage for reversible data hiding method based on contrast enhancement is proposed. Two improvements to the preprocessing stage are presented, which involve the analysis, merging, and shifting of the image histogram. The results show that the visual quality can be preserved after concealing data, and the embedding capacity can be maximized while minimizing the visual distortion.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Optics
Abhisek Paul, Paritosh Bhattacharya, Santi P. Maity
Summary: In this paper, a novel histogram modification-based bi histogram equalization (HE) approach is proposed for contrast enhancement in digital images. The proposed method successfully improves the visual quality of the images and its effectiveness is confirmed through quantitative measurements. Furthermore, comparative study shows that the suggested method outperforms other state-of-the-art techniques in image enhancement.
Article
Computer Science, Information Systems
X. Wu, Y. Sun, T. Kawanishi, K. Kashino
Summary: This study revisited 2D histogram equalization methods and proposed two novel contrast enhancement methods to address the challenge of consistent improvements in image brightness and contrast in different lighting conditions. By embedding inter-pixel contextual information of image reflectance into the 2D histogram and deriving an intensity mapping function, the proposed methods showed superior performance compared to existing methods. The use of image reflectance as a clue allowed for adaptive derivation of contrast enhancement degree for sufficient brightness improvement in low-light images and avoidance of excessive enhancement in normal-light images.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Xiuli Bi, Yixuan Shang, Bo Liu, Bin Xiao, Weisheng Li, Xinbo Gao
Summary: Contrast enhancement manipulation is a common method to improve the visual effect of an image, but it can also be considered a type of global image forgery. Detecting contrast enhancement manipulations is critical for global image forgery detection as it helps identify tampering attempts. Existing methods can only detect specific types of contrast enhancement manipulations, but our proposed zero-gap spans (ZGS) approach can explore and distinguish various contrast enhancement manipulations through image-level and patch-level classification, as well as estimate gamma values for gamma corrections.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2023)
Article
Multidisciplinary Sciences
Karishma Rao, Manu Bansal, Gagandeep Kaur
Summary: This paper presents a novel image enhancement technique for improving the contrast of color histopathology images. By utilizing retinex theory and local contrast adjustment, the proposed method combines adaptive weighting multiscale retinex with weighted contrast limited adaptive histogram equalization to enhance the quality of histopathology images. The results show that this method outperforms existing algorithms and is particularly useful for disease inspection and diagnosis.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2022)
Article
Multidisciplinary Sciences
Canlin Li, Jinjuan Zhu, Lihua Bi, Weizheng Zhang, Yan Liu
Summary: This paper proposes a new method for enhancing low-light images by balancing brightness and preserving details. The method involves bidirectional processing of the image, including double histogram equalization and total variation model extraction. The experimental results show that the proposed method outperforms existing methods in terms of visual effect.
Article
Optics
Liwei Chen, Yanyan Liu, Guoning Li, Jintao Hong, Jin Li, Jiantao Peng
Summary: A high-quality image enhancement algorithm is proposed in this paper to address the issues of noise amplification and excessive enhancement in low-illumination image enhancement. The algorithm utilizes the total-variation model, adaptive gamma transform, and improved multi-scale retinex algorithms to obtain enhanced images with reduced noise and preserved details. Experimental results demonstrate the effectiveness of the proposed algorithm in terms of reducing naturalness errors and achieving better visual effects.
JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION
(2023)
