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In this paper, we propose an end to end solution for image matting i.e high-precision extraction of foreground objects from natural images. Image matting and background detection can be achieved easily through chroma keying in a studio…

Computer Vision and Pattern Recognition · Computer Science 2020-03-26 Rishab Sharma , Rahul Deora , Anirudha Vishvakarma

This paper presents a novel context-aware image denoising algorithm that combines an adaptive image smoothing technique and color reduction techniques to remove perturbation from adversarial images. Adaptive image smoothing is achieved…

Computer Vision and Pattern Recognition · Computer Science 2021-01-18 Li-Yun Wang , Yeganeh Jalalpour , Wu-chi Feng

Enhancing low-light images while maintaining natural colors is a challenging problem due to camera processing variations and limited access to photos with ground-truth lighting conditions. The latter is a crucial factor for supervised…

Computer Vision and Pattern Recognition · Computer Science 2023-10-17 Wojciech Kozłowski , Michał Szachniewicz , Michał Stypułkowski , Maciej Zięba

As an efficient image contrast enhancement (CE) tool, adaptive gamma correction (AGC) was previously proposed by relating gamma parameter with cumulative distribution function (CDF) of the pixel gray levels within an image. ACG deals well…

Multimedia · Computer Science 2022-08-31 Gang Cao , Lihui Huang , Huawei Tian , Xianglin Huang , Yongbin Wang , Ruicong Zhi

Real camera footage is subject to noise, motion blur (MB) and depth of field (DoF). In some applications these might be considered distortions to be removed, but in others it is important to model them because it would be ineffective, or…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Siddhant Prakash , David R. Walton , Rafael K. dos Anjos , Anthony Steed , Tobias Ritschel

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

Image recognition models that work in challenging environments (e.g., extremely dark, blurry, or high dynamic range conditions) must be useful. However, creating training datasets for such environments is expensive and hard due to the…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Masakazu Yoshimura , Junji Otsuka , Atsushi Irie , Takeshi Ohashi

Consumer-grade camera systems often struggle to maintain stable image quality under complex illumination conditions such as low light, high dynamic range, and backlighting, as well as spatial color temperature variation. These issues lead…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Fuchen Li , Yansong Du , Wenbo Cheng , Xiaoxia Zhou , Sen Yin

This paper introduces a novel method for inter-camera color calibration for multispectral imaging with camera arrays using a consensus image. Capturing images using multispectral camera arrays has gained importance in medical, agricultural,…

Image and Video Processing · Electrical Eng. & Systems 2024-11-14 Katja Kossira , Jürgen Seiler , André Kaup

Natural image matting is an important problem in computer vision and graphics. It is an ill-posed problem when only an input image is available without any external information. While the recent deep learning approaches have shown promising…

Computer Vision and Pattern Recognition · Computer Science 2019-10-04 Qiqi Hou , Feng Liu

We present a method for harmonizing the lighting of a foreground video to match a target background scene, adjusting shadows, color tone, and illumination intensity (relightful harmonization). Unlike images, acquiring labeled data for…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Jun Myeong Choi , Jae Shin Yoon , Luchao Qi , Roni Sengupta , Joon-Young Lee

This paper presents a method for image relighting that enables precise and continuous control over multiple illumination attributes in a photograph. We formulate relighting as a conditional image generation task and introduce attribute…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Sumit Chaturvedi , Yannick Hold-Geoffroy , Mengwei Ren , Jingyuan Liu , He Zhang , Yiqun Mei , Julie Dorsey , Zhixin Shu

Enhancing images in low-light conditions is an important challenge in computer vision. Insufficient illumination negatively affects the quality of images, resulting in low contrast, intensive noise, and blurred details. This paper presents…

Image composition in image editing involves merging a foreground image with a background image to create a composite. Inconsistent lighting conditions between the foreground and background often result in unrealistic composites. Image…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Jiajie Li , Jian Wang , Chen Wang , Jinjun Xiong

Instance segmentation for low-light imagery remains largely unexplored due to the challenges imposed by such conditions, for example shot noise due to low photon count, color distortions and reduced contrast. In this paper, we propose an…

Computer Vision and Pattern Recognition · Computer Science 2025-04-11 Joanne Lin , Nantheera Anantrasirichai , David Bull

Accurate camera-to-lidar calibration is a requirement for sensor data fusion in many 3D perception tasks. In this paper, we present SceneCalib, a novel method for simultaneous self-calibration of extrinsic and intrinsic parameters in a…

Computer Vision and Pattern Recognition · Computer Science 2023-04-13 Ayon Sen , Gang Pan , Anton Mitrokhin , Ashraful Islam

Machine learning models trained on imbalanced datasets often exhibit intersectional biases-systematic errors arising from the interaction of multiple attributes such as object class and environmental conditions. This paper presents a…

Computer Vision and Pattern Recognition · Computer Science 2025-10-21 Farjana Yesmin

Low-light images are not conducive to human observation and computer vision algorithms due to their low visibility. Although many image enhancement techniques have been proposed to solve this problem, existing methods inevitably introduce…

Computer Vision and Pattern Recognition · Computer Science 2017-11-03 Zhenqiang Ying , Ge Li , Wen Gao

As an ever-increasing demand for high dynamic range (HDR) scene shooting, multi-exposure image fusion (MEF) technology has abounded. In recent years, multi-scale exposure fusion approaches based on detail-enhancement have led the way for…

Computer Vision and Pattern Recognition · Computer Science 2025-03-06 Xiaoning Liu

Real-world lighting often consists of multiple illuminants with different spectra. Separating and manipulating these illuminants in post-process is a challenging problem that requires either significant manual input or calibrated scene…

Computer Vision and Pattern Recognition · Computer Science 2017-11-28 Zhuo Hui , Kalyan Sunkavalli , Sunil Hadap , Aswin C. Sankaranarayanan