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BAYESIAN image superresolution AND HIDDEN VARIABLE MODELING

Journal of Systems Science & Complexity 2010年第1期23卷 116-136页

作者： Atsunori KANEMURA Shin-ichi MAEDA Wataru FUKUDA ShinI SHII Graduate School of Informatics Kyoto University

superresolution is an image processing technique that estimates an original high-resolutionimage from its low-resolution and degraded *** superresolution tasks,there have beenproblems regarding the computational cost for the estimation of high-dimensional *** are now being overcome by the recent development of fast computers and the developmentof powerful computational techniques such as variational Bayesian *** paper reviewsa Bayesian treatment of the superresolution problem and presents its extensions based on hierarchicalmodeling by employing hidden variables.

关键词： Bayesian estimation hidden variables image superresolution Markov random fields variational estimation.

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Dynamic Data Updating Algorithm for image superresolution Reconstruction

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Geo-Spatial Information Science 2006年第3期9卷 196-200页

作者： TAN Bing XU Qing ZHANG Yan XING Shuai Jiangnan Remote Sensing and Application Research Center 158 Shaoniancun RoadShanghai 200436China.

A dynamic data updating algorithm for image superesolution is proposed. On the basis of Delaunay triangulation and its local updating property, this algorithm can update the changed region directly under the circumstances that only a part of the source images has been changed. For its high efficiency and adaptability, this algorithm can serve as a fast algorithm for image superesolution reconstruction.

关键词： image superresolution image interpolation image registration Delaunay triangulation

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Non-blind super-resolution reconstruction for laser-induced damage dark-field imaging of optical elements

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Chinese Optics Letters 2024年第4期22卷 36-41页

作者：王倩陈凤东韩越越曾发路程刘国栋 Instrument Science and Technology Harbin Institute of TechnologyHarbin 150001China Research Center of Laser Fusion China Academy of Engineering PhysicsMianyang 621900China

The laser-induced damage detection images used in high-power laser facilities have a dark background,few textures with sparse and small-sized damage sites,and slight degradation caused by slight defocus and optical diffraction,which make the image superresolution(SR)reconstruction *** propose a non-blind SR reconstruction method by using an exquisite mixing of high-,intermediate-,and low-frequency information at each stage of pixel reconstruction based on *** simplify the channel attention mechanism and activation function to focus on the useful channels and keep the global information in the *** pay more attention on the damage area in the loss function of our end-toend deep neural *** constructing a high-low resolution image pairs data set,we precisely measure the point spread function(PSF)of a low-resolution imaging system by using a Bernoulli calibration pattern;the influence of different distance and lateral position on PSFs is also considered.A high-resolution camera is used to acquire the ground-truth images,which is used to create a low-resolution image pairs data set by convolving with the measured *** on the data set,our network has achieved better results,which proves the effectiveness of our method.

关键词： laser-induced damage image superresolution image segmentation

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维普期刊数据库

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