中国科学院机构知识库网格系统: 检索

Robust HDR reconstruction using 3D patch based on two-scale decomposition 期刊论文 OAI收割
Signal Processing, 2024, 卷号: 219
作者: Qiao, Zhangchi; Yi, Hongwei; Wen, Desheng; Han, Yong

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收藏 | 浏览/下载：23/0 | 提交时间：2024/03/07

High dynamic range imaging Multi-exposure image fusion Two-scale features Patch-based match Dynamic/multi-view scene

Deciphering the neural mechanisms of miR-134 in major depressive disorder with population-based and person-specific imaging transcriptomic techniques 期刊论文 OAI收割
PSYCHIATRY RESEARCH, 2023, 卷号: 329, 页码: 12
作者: Lou, Jing; Liu, Kai; Wen, Junyan; He, Yini; Sun, Yuqing

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收藏 | 浏览/下载：21/0 | 提交时间：2024/02/22

Major depressive disorder (MDD) miR-134 Two -stage cross -scale imaging transcriptomic analyses Biomarkers Multi-omics

A painting authentication method based on multi-scale spatial-spectral feature fusion and convolutional neural network 会议论文 OAI收割
Hybrid, Wuhan, China, 2023-12-15
作者: Ren, Zeyue; Wang, Huawei; Kong, Fanzi; Liu, Qing; Yang, Yongqing

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收藏 | 浏览/下载：2/0 | 提交时间：2024/09/12

Painting authentication Hyperspectral imaging Multi-scale fusion Efficientnet v2

Multi-scale multi-dimensional characterization of clay-hosted pore networks of shale using FIBSEM, TEM, and X-ray micro-tomography: Implications for methane storage and migration 期刊论文 OAI收割
APPLIED CLAY SCIENCE, 2021, 卷号: 213, 页码: 15
作者: Zhu, Hongjian; Huang, Cheng; Ju, Yiwen; Bu, Hongling; Li, Xiaoshi

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收藏 | 浏览/下载：76/0 | 提交时间：2021/11/01

Shale gas reservoirs Multi-scale imaging Clay-hosted pore Gas storage and migration

Automatic lumbar spinal MRI image segmentation with a multi-scale attention network 期刊论文 OAI收割
Neural Computing and Applications, 2021, 卷号: 33, 期号: 18, 页码: 11589-11602
作者: Li HX(李海星); Luo HB(罗海波); Wang H(王欢); Shi ZL(史泽林); Yan CN(阎崇楠)

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收藏 | 浏览/下载：28/0 | 提交时间：2021/03/31

Lumbar spinal stenosis Magnetic resonance imaging image Deep learning Dual-branch multi-scale attention module Feature extraction

Learning Non-Local Spatial Correlations to Restore Sparse 3D Single-Photon Data 期刊论文 OAI收割
IEEE Transactions on Image Processing, 2020, 卷号: 29, 页码: 3119-3131
作者: Chen, Songmao; Halimi, Abderrahim; Ren, Ximing; McCarthy, Aongus; Su, Xiuqin

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收藏 | 浏览/下载：58/0 | 提交时间：2020/03/10

Single photon 3D Lidar imaging Poisson statistics image restoration ADMM Laplacian regularization graph,non-uniform sampling multi-scale analysis

Design of monocentric wide field-of-view and high-resolution computational imaging system 期刊论文 OAI收割
Acta Physica Sinica, 2019, 卷号: 68, 期号: 8, 页码: 10
作者: F.Liu; Y.Z.Wei; P.L.Han; J.W.Liu; X.P.Shao

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收藏 | 浏览/下载：46/0 | 提交时间：2020/08/24

wide field of view and high-resolution imaging system,computational,imaging,optical system design,multi-scale imaging,Physics

Tone mapping infrared images using conditional filtering based multi-scale retinex 会议论文 OAI收割
Conference on Applied Optics and Photonics (AOPC) - Image Processing and Analysis, Beijing, MAY 05-07, 2015
作者: Luo HB(罗海波); Xu LY(许凌云); Hui B(惠斌); Chang Z(常铮)

收藏 | 浏览/下载：30/0 | 提交时间：2015/11/18

Tone mapping High dynamic rage image infrared imaging Multi-scale retinex Image enhancement Conditional Gaussian Filter (CGF) Conditional Filtering Based Multi-Scale Retinex(CFBMSR)

An improved infrared image enhancement algorithm based on multi-scale decomposition 会议论文 OAI收割
International Symposium on Optoelectronic Technology and Application 2014, Beijing, China, May 13-15, 2014
作者: Zhang HH(张红辉); Luo HB(罗海波)

收藏 | 浏览/下载：45/0 | 提交时间：2014/12/29

infrared imaging multi-scale nonlinear amplification image enhancement

A line mapping based automatic registration algorithm of infrared and visible images 会议论文 OAI收割
5th International Symposium on Photoelectronic Detection and Imaging (ISPDI) - Infrared Imaging and Applications, Beijing, June 25-27, 2013
作者: Ai R(艾锐); Shi ZL(史泽林); Xu DJ(徐德江); Zhang CS(张程硕)

收藏 | 浏览/下载：36/0 | 提交时间：2013/12/26

There exist complex gray mapping relationships among infrared and visible images because of the different imaging mechanisms. The difficulty of infrared and visible image registration is to find a reasonable similarity definition. In this paper, we develop a novel image similarity called implicit linesegment similarity(ILS) and a registration algorithm of infrared and visible images based on ILS. Essentially, the algorithm achieves image registration by aligning the corresponding line segment features in two images. First, we extract line segment features and record their coordinate positions in one of the images, and map these line segments into the second image based on the geometric transformation model. Then we iteratively maximize the degree of similarity between the line segment features and correspondence regions in the second image to obtain the model parameters. The advantage of doing this is no need directly measuring the gray similarity between the two images. We adopt a multi-resolution analysis method to calculate the model parameters from coarse to fine on Gaussian scale space. The geometric transformation parameters are finally obtained by the improved Powell algorithm. Comparative experiments demonstrate that the proposed algorithm can effectively achieve the automatic registration for infrared and visible images, and under considerable accuracy it makes a more significant improvement on computational efficiency and anti-noise ability than previously proposed algorithms.