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Current image harmonization methods consider the entire background as the guidance for harmonization. However, this may limit the capability for user to choose any specific object/person in the background to guide the harmonization. To…

Computer Vision and Pattern Recognition · Computer Science 2022-03-17 Jeya Maria Jose Valanarasu , He Zhang , Jianming Zhang , Yilin Wang , Zhe Lin , Jose Echevarria , Yinglan Ma , Zijun Wei , Kalyan Sunkavalli , Vishal M. Patel

The quality of images captured in outdoor environments can be affected by poor weather conditions such as fog, dust, and atmospheric scattering of other particles. This problem can bring extra challenges to high-level computer vision tasks…

Computer Vision and Pattern Recognition · Computer Science 2019-04-19 Jiaxi He , Frank Z. Xing , Ran Yang , Cishen Zhang

Image inpaiting is an important task in image processing and vision. In this paper, we develop a general method for patch-based image inpainting by synthesizing new textures from existing one. A novel framework is introduced to find several…

Computer Vision and Pattern Recognition · Computer Science 2016-05-06 Tao Zhou , Brian Johnson , Rui Li

Shadow detection is a challenging task as it requires a comprehensive understanding of shadow characteristics and global/local illumination conditions. We observe from our experiment that state-of-the-art deep methods tend to have higher…

Computer Vision and Pattern Recognition · Computer Science 2024-02-22 Huankang Guan , Ke Xu , Rynson W. H. Lau

In this paper, we propose a novel algorithm to rectify illumination of the digitized documents by eliminating shading artifacts. Firstly, a topographic surface of an input digitized document is created using luminance value of each pixel.…

Computer Vision and Pattern Recognition · Computer Science 2019-05-06 Seungjun Jung , Muhammad Abul Hasan , Changick Kim

Modern camera pipelines apply extensive on-device processing, such as exposure adjustment, white balance, and color correction, which, while beneficial individually, often introduce photometric inconsistencies across views. These appearance…

Computer Vision and Pattern Recognition · Computer Science 2025-10-01 Jisu Shin , Richard Shaw , Seunghyun Shin , Zhensong Zhang , Hae-Gon Jeon , Eduardo Perez-Pellitero

Removing reflection artefacts from a single image is a problem of both theoretical and practical interest, which still presents challenges because of the massively ill-posed nature of the problem. In this work, we propose a technique based…

Computer Vision and Pattern Recognition · Computer Science 2019-10-02 Daniel Heydecker , Georg Maierhofer , Angelica I. Aviles-Rivero , Qingnan Fan , Dongdong Chen , Carola-Bibiane Schönlieb , Sabine Süsstrunk

This thesis surveys the research in patch-based synthesis and algorithms for finding correspondences between small local regions of images. We additionally explore a large kind of applications of this new fast randomized matching technique.…

Graphics · Computer Science 2020-05-14 Hadi Abdi Khojasteh

Purpose: To remove retinal shadows from optical coherence tomography (OCT) images of the optic nerve head(ONH). Methods:2328 OCT images acquired through the center of the ONH using a Spectralis OCT machine for both eyes of 13 subjects were…

Hazy images are common in real scenarios and many dehazing methods have been developed to automatically remove the haze from images. Typically, the goal of image dehazing is to produce clearer images from which human vision can better…

Computer Vision and Pattern Recognition · Computer Science 2018-10-16 Yanting Pei , Yaping Huang , Qi Zou , Yuhang Lu , Song Wang

Haze and fog reduce the visibility of outdoor scenes as a veil like semi-transparent layer appears over the objects. As a result, images captured under such conditions lack contrast. Image dehazing methods try to alleviate this problem by…

Computer Vision and Pattern Recognition · Computer Science 2018-11-28 Shirsendu Sukanta Halder , Sanchayan Santra , Bhabatosh Chanda

Image composition is an important operation in image processing, but the inconsistency between foreground and background significantly degrades the quality of composite image. Image harmonization, which aims to make the foreground…

Computer Vision and Pattern Recognition · Computer Science 2020-03-23 Wenyan Cong , Jianfu Zhang , Li Niu , Liu Liu , Zhixin Ling , Weiyuan Li , Liqing Zhang

We propose Diff-Shadow, a global-guided diffusion model for shadow removal. Previous transformer-based approaches can utilize global information to relate shadow and non-shadow regions but are limited in their synthesis ability and recover…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Jinting Luo , Ru Li , Chengzhi Jiang , Xiaoming Zhang , Mingyan Han , Ting Jiang , Haoqiang Fan , Shuaicheng Liu

All existing image enhancement methods, such as HDR tone mapping, cannot recover A/D quantization losses due to insufficient or excessive lighting, (underflow and overflow problems). The loss of image details due to A/D quantization is…

Computer Vision and Pattern Recognition · Computer Science 2018-03-22 Chang Liu , Xiaolin Wu , Xiao Shu

Single image haze removal is an extremely challenging problem due to its inherent ill-posed nature. Several prior-based and learning-based methods have been proposed in the literature to solve this problem and they have achieved superior…

Computer Vision and Pattern Recognition · Computer Science 2019-04-23 He Zhang , Vishwanath Sindagi , Vishal M. Patel

Image matting is generally modeled as a space transform from the color space to the alpha space. By estimating the alpha factor of the model, the foreground of an image can be extracted. However, there is some dimensional information…

Computer Vision and Pattern Recognition · Computer Science 2019-04-17 Xuelong Li , Kang Liu , Yongsheng Dong , Dacheng Tao

This paper proposes a novel image contrast enhancement method based on both a noise aware shadow-up function and Retinex (retina and cortex) decomposition. Under low light conditions, images taken by digital cameras have low contrast in…

Computer Vision and Pattern Recognition · Computer Science 2018-11-09 Chien Cheng Chien , Yuma Kinoshita , Sayaka Shiota , Hitoshi Kiya

Many low-light enhancement methods ignore intensive noise in original images. As a result, they often simultaneously enhance the noise as well. Furthermore, extra denoising procedures adopted by most methods ruin the details. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2018-05-01 Xutong Ren , Mading Li , Wen-Huang Cheng , Jiaying Liu

We present a new algorithm for multi-region segmentation of 2D images with objects that may partially occlude each other. Our algorithm is based on the observation hat human performance on this task is based both on prior knowledge about…

Computer Vision and Pattern Recognition · Computer Science 2016-06-16 Yuka Kihara , Matvey Soloviev , Tsuhan Chen

We develop a framework for extracting a concise representation of the shape information available from diffuse shading in a small image patch. This produces a mid-level scene descriptor, comprised of local shape distributions that are…

Computer Vision and Pattern Recognition · Computer Science 2015-04-15 Ying Xiong , Ayan Chakrabarti , Ronen Basri , Steven J. Gortler , David W. Jacobs , Todd Zickler