Article
Chemistry, Analytical
Yumei Li, Ningfang Liao, Wenmin Wu, Chenyang Deng, Yasheng Li, Qiumei Fan, Chuanjie Liu
Summary: This study aims to solve the difficulties in displaying high dynamic range (HDR) images on conventional standard display devices. The proposed modified tone-mapping operator (TMO), called iCAM06-m, combines iCAM06 and a multi-scale enhancement algorithm to compensate for saturation and hue drift. Subjective evaluation shows the better performance of iCAM06-m compared to other TMOs, confirming the effectiveness of chroma compensation and multi-scale decomposition. The proposed algorithm overcomes the limitations of other algorithms and is a good candidate for a general purpose TMO.
Article
Computer Science, Information Systems
Imran Mehmood, Xinye Shi, Muhammad Usman Khan, Ming Ronnier Luo
Summary: One of the key challenges in tone mapping is to preserve the perceptual quality of high dynamic range (HDR) images when mapping them to standard dynamic range (SDR) displays. This research proposes a new tone mapping operator (TMOz) that leverages CIECAM16 perceptual attributes to achieve more optimal colorfulness reproduction. Both objective and subjective evaluations show that the proposed model outperforms existing TMO algorithms.
Article
Computer Science, Hardware & Architecture
Tian Yuan, Chen Li, Lihua Tian, Guo Li
Summary: Recent years have seen significant progress in image quality assessment, especially in the field of no-reference (NR)-IQA with the development of deep learning. The proposed framework in this study utilizes a range mapping method to enhance the accuracy and generalization of NR-IQA models by mapping existing full-reference (FR)-IQA datasets to NR-IQA datasets. Experimental results using the largest available datasets have confirmed the effectiveness of this approach.
COMPUTERS & ELECTRICAL ENGINEERING
(2021)
Review
Engineering, Electrical & Electronic
Xueyu Han, Ishtiaq Rasool Khan, Susanto Rahardja
Summary: Compared to conventional digital imaging, high dynamic range (HDR) image tone mapping technology faithfully reproduces real-world scenes on common displays for enhanced viewing experience. This paper presents a literature review and benchmarks of existing tone mapping methods, providing updated information and paving the way for further developments in the field.
DIGITAL SIGNAL PROCESSING
(2023)
Article
Chemistry, Analytical
Ivana Shopovska, Ana Stojkovic, Jan Aelterman, David Van Hamme, Wilfried Philips
Summary: Intelligent driver assistance systems are increasingly popular and have the ability to detect vulnerable road users. However, standard imaging sensors perform poorly in strong illumination contrast conditions. This study focuses on the use of HDR imaging sensors and the need for tone mapping in vehicle perception systems. The proposed DI-TM method achieves the best performance in terms of detection metrics in challenging dynamic range conditions, with a 13% improvement compared to existing methods.
Article
Engineering, Electrical & Electronic
Weihao Xia, Yujiu Yang, Jing-Hao Xue, Jing Xiao
Summary: This study introduces a new no-reference image quality assessment method, incorporating the concept of domain fingerprint. By designing a new domain-aware architecture, the method is able to simultaneously determine the distortion sources and quality of an image. Experimental results show that the proposed method outperforms most existing state-of-the-art NR-IQA methods.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Jie Song, Mengjun Liu
Summary: This paper proposes a new methodology to convert a full-reference focus quality assessment metric into a no-reference one. The methodology includes three hypotheses that describe the relationship between focus quality of the original image and its variants. Two no-reference metrics are constructed using this methodology, one using Brenner Gradient and the other using a full-reference metric proposed by the authors. Evaluation is conducted on both a public dataset and a proposed dataset, showing that the second metric exhibits the best performance with comparable calculation time to some fastest metrics considered. (c) 2023 Elsevier Ltd. All rights reserved.
PATTERN RECOGNITION
(2023)
Article
Computer Science, Information Systems
Jiachen Yang, Yanshuang Zhou, Yang Zhao, Jiabao Wen
Summary: This paper proposes a quality assessment method for tone-mapped images based on generating multi-exposure sequences. By using a generative adversarial network to generate sequences with different exposure levels and utilizing a convolutional neural network to extract features and learn mapping relationships, the proposed method achieves quality assessment of tone-mapped images.
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
(2022)
Article
Engineering, Electrical & Electronic
Yang Zhao, Shuai Xiao, Jiachen Yang, Wen Lu, Xinbo Gao
Summary: This paper introduces a method for accurately predicting the quality of TMIs: RETI. Based on the characteristics of HDR images, three important elements including authenticity, energy and information preservation, and scene expressiveness are considered, combined with subjective quality for training. The results show that the method has good prediction and generalization abilities compared to some state-of-the-art methods.
Article
Telecommunications
Xiaoyu Ma, Suiyu Zhang, Chang Liu, Dingguo Yu
Summary: Blind image quality assessment (BIQA) is a fundamental problem in low-level computer vision. Deep neural networks have been increasingly used for BIQA. However, training deep convolutional neural networks (DCNN) often requires massive annotated data, which is lacking in BIQA. To address this, a totally opinion-unaware BIQA method was proposed, which avoids subjective annotations during training. Multiple full-reference image quality assessment (FR-IQA) metrics are used to label distorted images, and a deep neural network (DNN) is trained to predict the multiple FR-IQA scores blindly. Finally, an adversarial auto-encoder is used to aggregate the predictions into a final quality score.
CHINA COMMUNICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Baoliang Chen, Lingyu Zhu, Chenqi Kong, Hanwei Zhu, Shiqi Wang, Zhu Li
Summary: In this paper, a no-reference image quality assessment method based on feature level pseudo-reference hallucination is proposed. The method utilizes perceptually meaningful features to characterize visual quality and leverages natural image statistical behaviors for accurate predictions. Experimental results demonstrate the effectiveness and high generalization capability of the proposed method on multiple databases.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2022)
Article
Engineering, Electrical & Electronic
Neeraj Badal, Rajiv Soundararajan, Ankur Garg, Abhishek Patil
Summary: Pansharpening is a process that enhances the spatial resolution of a multispectral image using a high-resolution panchromatic image. Quality assessment of pansharpened images is crucial for the analysis and design of pansharpening methods. This article focuses on predicting the quality in a no-reference setting and proposes a learning-based approach for image quality assessment.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Computer Science, Information Systems
Zahi Al Chami, Chady Abou Jaoude, Richard Chbeir, Mahmoud Barhamgi, Mansour Naser Alraja
Summary: This paper presents a framework for processing a large number of images, which can real-time estimate and assist in enhancing image quality. The quality evaluation is conducted using Convolutional Neural Network and other methods to achieve both No-Reference and Full-Reference quality assessment, enhanced with a Super-Resolution Model.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Jiaqi Zhang, Zhigao Fang, Lu Yu
Summary: The rapid development of deep learning-based image compression techniques presents new challenges for objective image quality assessment. To address this, researchers have built a database and proposed a two-step deep learning model for compressed image quality assessment, achieving better performance than traditional methods.
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
(2022)
Article
Computer Science, Artificial Intelligence
Juan Wang, Zewen Chen, Chunfeng Yuan, Bing Li, Wentao Ma, Weiming Hu
Summary: This paper proposes a hierarchical curriculum learning (HCL) framework for no-reference image quality assessment (NR-IQA). The framework leverages external data to learn prior knowledge about IQA and achieves state-of-the-art performance on multiple authentic IQA datasets.
INTERNATIONAL JOURNAL OF COMPUTER VISION
(2023)
Article
Automation & Control Systems
Tianwei Zhou, Zhiqiang Zuo, Yijing Wang
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2020)
Article
Engineering, Electrical & Electronic
Guanghui Yue, Chunping Hou, Tianwei Zhou, Xinfeng Zhang
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2019)
Article
Computer Science, Information Systems
Guanghui Yue, Chunping Hou, Ke Gu, Tianwei Zhou, Hantao Liu
IEEE TRANSACTIONS ON MULTIMEDIA
(2019)
Article
Automation & Control Systems
Tianwei Zhou, Zhiqiang Zuo, Yijing Wang
Summary: This paper introduces a novel active event-triggered control scheme for nonlinear networked control systems with quantizer, network-induced delay, and packet dropout. By considering the structure of the hysteresis quantizer and actively compensating for the negative effects of network-induced delay and potential packet dropout, the proposed method achieves a more balanced updating frequency and reduced total triggering.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Automation & Control Systems
Tianwei Zhou, Zhiqiang Zuo, Yijing Wang, Hongchao Li
Summary: This article discusses the synchronization problem of drive-response Lurie systems with sampled output error transmitted through a limited network channel with one-step packet dropout. Two strategies are proposed to actively deal with the negative effects caused by packet dropout and sampling sensor, ensuring synchronization and keeping the output error bounded by the quantizer range. The relationship between the sensor sampling interval and the triggering parameter is provided to match with the proposed methods, along with a lower transmission bit rate to save more channel resources. An example of synchronizing two Chua's circuits is used to demonstrate the validity of the presented results.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
