Results 181 to 190 of about 8,378,989 (251)

Image Super-Resolution Via Sparse Representation

IEEE Transactions on Image Processing, 2010
This paper presents a new approach to single-image super-resolution, based on sparse signal representation. Research on image statistics suggests that image patches can be well-represented as a sparse linear combination of elements from an appropriately chosen over-complete dictionary.
Yang, Jianchao, Wright, John, Huang, Thomas S., Ma, Yi   +3 more
openaire   +3 more sources

Image Representation

Data Science for Nano Image Analysis, 2011
Chiwoo Park, Yu Ding
openaire   +2 more sources

SphereSR: $360^{\circ}$ Image Super-Resolution with Arbitrary Projection via Continuous Spherical Image Representation

Computer Vision and Pattern Recognition, 2021
The $360^{\circ}$ imaging has recently gained much attention; however, its angular resolution is relatively lower than that of a narrow field-of-view (FOV) perspective image as it is captured using a fisheye lens with the same sensor size.
Youngho Yoon, Inchul Chung, Lin Wang, Kuk-Jin Yoon   +3 more
semanticscholar   +1 more source

Improved image representation and sparse representation for image classification

Applied Intelligence, 2020
It seems that for multiple available images of the same object, the pixel values at the same image position are almost always different, which is especially obvious for the deformable object. This implies that it will be not easy to correctly classify the deformable object.
Shijun Zheng, Yongjun Zhang, Wenjie Liu, Yongjie Zou   +3 more
openaire   +1 more source

SpineParseNet: Spine Parsing for Volumetric MR Image by a Two-Stage Segmentation Framework With Semantic Image Representation

IEEE Transactions on Medical Imaging, 2020
Spine parsing (i.e., multi-class segmentation of vertebrae and intervertebral discs (IVDs)) for volumetric magnetic resonance (MR) image plays a significant role in various spinal disease diagnoses and treatments of spine disorders, yet is still a ...
Shumao Pang, Chunlan Pang, Lei Zhao, Yang Chen, Zhihai Su, Yujia Zhou, Meiyan Huang, Wei Yang, Hai Lu, Qianjin Feng   +9 more
semanticscholar   +1 more source

Holographic representations of images

IEEE Transactions on Image Processing, 1998
We discuss a new type of holographic image representations that have advantages in a "distributed" world. We call these representations holographic. Arbitrary portions of a holographic representation enable reconstruction of the whole image, with distortions that decrease gradually with the increase in the size of the portions available.
A M, Bruckstein, R J, Holt, A N, Netravali   +2 more
openaire   +2 more sources

VisualEchoes: Spatial Image Representation Learning through Echolocation

European Conference on Computer Vision, 2020
Several animal species (e.g., bats, dolphins, and whales) and even visually impaired humans have the remarkable ability to perform echolocation: a biological sonar used to perceive spatial layout and locate objects in the world.
Ruohan Gao, Changan Chen, Ziad Al-Halah, Carl Schissler, K. Grauman   +4 more
semanticscholar   +1 more source

Image representation of pose-transition feature for 3D skeleton-based action recognition

Information Sciences, 2020
Recently, skeleton-based human action recognition has received more interest from industrial and research communities for many practical applications thanks to the popularity of depth sensors.
Thien Huynh-The, Cam-Hao Hua, T. Ngo, Dong-Seong Kim   +3 more
semanticscholar   +1 more source

GaussianImage: 1000 FPS Image Representation and Compression by 2D Gaussian Splatting

European Conference on Computer Vision
Implicit neural representations (INRs) recently achieved great success in image representation and compression, offering high visual quality and fast rendering speeds with 10-1000 FPS, assuming sufficient GPU resources are available.
Xinjie Zhang, Xingtong Ge, Tongda Xu, Dailan He, Yan Wang, Hongwei Qin, Guo Lu, Jing Geng, Jun Zhang   +8 more
semanticscholar   +1 more source

Tensor Convolution-Like Low-Rank Dictionary for High-Dimensional Image Representation

IEEE transactions on circuits and systems for video technology (Print)
High-dimensional image representation is a challenging task since data has the intrinsic low-dimensional and shift-invariant characteristics. Currently, popular methods, such as tensor-Singular Value Decomposition (t-SVD), have limited ability in ...
Jize Xue, Yongqiang Zhao, Tongle Wu, Jonathan Cheung-Wai Chan   +3 more
semanticscholar   +1 more source