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This paper proposes a novel multi-exposure image fusion method based on exposure compensation. Multi-exposure image fusion is a method to produce images without color saturation regions, by using photos with different exposures. However, in…

Computer Vision and Pattern Recognition · Computer Science 2018-06-27 Yuma Kinoshita , Taichi Yoshida , Sayaka Shiota , Hitoshi Kiya

We propose a novel method for adjusting luminance for multi-exposure image fusion. For the adjustment, two novel scene segmentation approaches based on luminance distribution are also proposed. Multi-exposure image fusion is a method for…

Multimedia · Computer Science 2019-04-23 Yuma Kinoshita , Hitoshi Kiya

This paper proposes a novel luminance adjustment method based on automatic exposure compensation for multi-exposure image fusion. Multi-exposure image fusion is a method to produce images without saturation regions, by using photos with…

Computer Vision and Pattern Recognition · Computer Science 2018-05-30 Yuma Kinoshita , Sayaka Shiota , Hitoshi Kiya

Due to the low accuracy of object detection and recognition in many intelligent surveillance systems at nighttime, the quality of night images is crucial. Compared with the corresponding daytime image, nighttime image is characterized as…

Computer Vision and Pattern Recognition · Computer Science 2023-07-12 Xinyi Bai , Steffi Agino Priyanka , Hsiao-Jung Tung , Yuankai Wang

Low light very likely leads to the degradation of an image's quality and even causes visual task failures. Existing image enhancement technologies are prone to overenhancement, color distortion or time consumption, and their adaptability is…

Image and Video Processing · Electrical Eng. & Systems 2022-05-17 Xiaozhou Lei , Zixiang Fei , Wenju Zhou , Huiyu Zhou , Minrui Fei

This paper proposes a novel pseudo multi-exposure image fusion method based on a single image. Multi-exposure image fusion is used to produce images without saturation regions, by using photos with different exposures. However, it is…

Computer Vision and Pattern Recognition · Computer Science 2018-11-14 Yuma Kinoshita , Sayaka Shiota , Hitoshi Kiya

The human visual perception system has strong robustness in image fusion. This robustness is based on human visual perception system's characteristics of feature selection and non-linear fusion of different features. In order to simulate…

Computer Vision and Pattern Recognition · Computer Science 2020-06-23 Aiqing Fang , Xinbo Zhao , Jiaqi Yang , Yanning Zhang

Exposure correction is one of the fundamental tasks in image processing and computational photography. While various methods have been proposed, they either fail to produce visually pleasing results, or only work well for limited types of…

Computer Vision and Pattern Recognition · Computer Science 2019-10-31 Qing Zhang , Yongwei Nie , Wei-Shi Zheng

This paper presents an algorithm that enhances undesirably illuminated images by generating and fusing multi-level illuminations from a single image.The input image is first decomposed into illumination and reflectance components by using…

Computer Vision and Pattern Recognition · Computer Science 2017-08-03 Jae Sung Park , Nam Ik Cho

High Dynamic Range (HDR) imaging aims to reproduce the wide range of brightness levels present in natural scenes, which the human visual system can perceive but conventional digital cameras often fail to capture due to their limited dynamic…

Image and Video Processing · Electrical Eng. & Systems 2025-10-28 Kumbha Nagaswetha

A novel method of contrast enhancement is proposed for underexposed images, in which heavy noise is hidden. Under low light conditions, images taken by digital cameras have low contrast in dark or bright regions. This is due to a limited…

Multimedia · Computer Science 2019-04-26 Chien-Cheng Chien , Yuma Kinoshita , Hitoshi Kiya

A small ISO and a small exposure time are usually used to capture an image in the back or low light conditions which results in an image with negligible motion blur and small noise but look dark. In this paper, a single image brightening…

Computer Vision and Pattern Recognition · Computer Science 2020-07-27 Chaobing Zheng , Zhengguo Li , Yi Yang , Shiqian Wu

Contrast enhancement and noise removal are coupled problems for low-light image enhancement. The existing Retinex based methods do not take the coupling relation into consideration, resulting in under or over-smoothing of the enhanced…

Image and Video Processing · Electrical Eng. & Systems 2019-11-27 Yang Wang , Yang Cao , Zheng-Jun Zha , Jing Zhang , Zhiwei Xiong , Wei Zhang , Feng Wu

Low-light imaging with handheld mobile devices is a challenging issue. Limited by the existing models and training data, most existing methods cannot be effectively applied in real scenarios. In this paper, we propose a new low-light image…

Image and Video Processing · Electrical Eng. & Systems 2021-03-02 Meng Chang , Huajun Feng , Zhihai Xu , Qi Li

Previous raw image-based low-light image enhancement methods predominantly relied on feed-forward neural networks to learn deterministic mappings from low-light to normally-exposed images. However, they failed to capture critical…

Computer Vision and Pattern Recognition · Computer Science 2023-08-16 Yufei Wang , Yi Yu , Wenhan Yang , Lanqing Guo , Lap-Pui Chau , Alex C. Kot , Bihan Wen

Images acquired by computer vision systems under low light conditions have multiple characteristics like high noise, lousy illumination, reflectance, and bad contrast, which make object detection tasks difficult. Much work has been done to…

Computer Vision and Pattern Recognition · Computer Science 2021-08-02 Winston Chen , Tejas Shah

In addition to low light, night images suffer degradation from light effects (e.g., glare, floodlight, etc). However, existing nighttime visibility enhancement methods generally focus on low-light regions, which neglects, or even amplifies…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Shufan Pei , Junhong Lin , Wenxi Liu , Tiesong Zhao , Chia-Wen Lin

Recent innovations shows that blending of details captured by single Low Dynamic Range (LDR) sensor overcomes the limitations of standard digital cameras to capture details from high dynamic range scene. We present a method to produce…

Computer Vision and Pattern Recognition · Computer Science 2022-07-12 Harbinder Singh , Dinesh Arora , Vinay Kumar

High dynamic range (HDR) imaging enables to immortalize natural scenes similar to the way that they are perceived by human observers. With regular low dynamic range (LDR) capture/display devices, significant details may not be preserved in…

Computer Vision and Pattern Recognition · Computer Science 2021-05-26 Diclehan Karakaya , Oguzhan Ulucan , Mehmet Turkan

Images captured underwater often suffer from suboptimal illumination settings that can hide important visual features, reducing their quality. We present a novel single-image low-light underwater image enhancer, L^2UWE, that builds on our…

Computer Vision and Pattern Recognition · Computer Science 2020-11-09 Tunai Porto Marques , Alexandra Branzan Albu
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