Search

Your search keyword '"Shi, Guokai"' showing total 13 results
Start Over Author "Shi, Guokai" Search Limiters Available in Library Collection
13 results on '"Shi, Guokai"'

2. Spectral-Wise Implicit Neural Representation for Hyperspectral Image Reconstruction

Author

Chen, Huan, Zhao, Wangcai, Xu, Tingfa, Shi, Guokai, Zhou, Shiyun, Liu, Peifu, and Li, Jianan

Abstract

Coded Aperture Snapshot Spectral Imaging (CASSI) reconstruction aims to recover the 3D spatial-spectral signal from 2D measurement. Existing methods for reconstructing Hyperspectral Image (HSI) typically involve learning mappings from a 2D compressed image to a predetermined set of discrete spectral bands. However, this approach overlooks the inherent continuity of the spectral information. In this study, we propose an innovative method called Spectral-wise Implicit Neural Representation (SINR) as a pioneering step toward addressing this limitation. SINR introduces a continuous spectral amplification process for HSI reconstruction, enabling spectral super-resolution with customizable magnification factors. To achieve this, we leverage the concept of implicit neural representation. Specifically, our approach introduces a spectral-wise attention mechanism that treats individual channels as distinct tokens, thereby capturing global spectral dependencies. Additionally, our approach incorporates two components, namely a Fourier coordinate encoder and a spectral scale factor module. The Fourier coordinate encoder enhances the SINR’s ability to emphasize high-frequency components, while the spectral scale factor module guides the SINR to adapt to the variable number of spectral channels. Notably, the SINR framework enhances the flexibility of CASSI reconstruction by accommodating an unlimited number of spectral bands in the desired output. Extensive experiments demonstrate that our SINR outperforms baseline methods. By enabling continuous reconstruction within the CASSI framework, we take the initial stride toward integrating implicit neural representation into the field.

Published
2024
Full Text
View/download PDF

6. Local Phase-Amplitude Joint Correction for Free Surface Velocity of Hopkinson Pressure Bar

Author

De-zhi Zhang, Hai-bin Xu, Min Zhang, Junhua He, Jun Yang, Yang Zhang, Shi Guokai, and Wen-xiang Liu

Subjects
Shock wave, Propagation time, Bar (music), 020101 civil engineering, 02 engineering and technology, 01 natural sciences, lcsh:Technology, 0201 civil engineering, 010309 optics, lcsh:Chemistry, Hopkinson pressure bar, 0103 physical sciences, General Materials Science, Dispersion (water waves), Instrumentation, propagation mode, lcsh:QH301-705.5, Blast wave, Fluid Flow and Transfer Processes, Physics, lcsh:T, Process Chemistry and Technology, General Engineering, Mechanics, explosive shock wave, explosion mechanics, lcsh:QC1-999, Computer Science Applications, Amplitude, lcsh:Biology (General), lcsh:QD1-999, lcsh:TA1-2040, Group velocity, Phase velocity, lcsh:Engineering (General). Civil engineering (General), lcsh:Physics, Pochhammer–Chree theory
Abstract

The Hopkinson pressure bar is widely used to measure the reflected pressure of blast waves over a short distance. However, dispersion effects will occur when the elastic stress waves propagate in the pressure bar due to lateral inertia, and there will be errors between the signals obtained from the sensors and the actual loading. For the free surface velocity measured in our system, we developed a local phase-amplitude joint correction method to convert the measured velocity into the average reflected pressure of a shock wave at the impact end of the bar, considering factors such as propagation modes of the elastic wave, the frequency components&rsquo, time of arrival, velocity variation over the bar axis, and the stress&ndash, velocity relationship. Firstly, the Pochhammer&ndash, Chree frequency equation is calculated numerically, and the first to fourth orders of phase velocity, group velocity, normalized frequency, and propagation time curves of elastic wave propagation in 35CrMnSiA steel are obtained. Secondly, the phase and amplitude correction formulas for calculating average reflected pressure from center velocity are derived based on the propagation mode of the axial elastic wave in the pressure bar by analyzing the time-frequency combined spectrum obtained by short-time Fourier transform. Thirdly, a local phase-amplitude joint correction algorithm based on propagation mode is proposed in detail. The experimental tests and data analyses are carried out for eight sets of pressure bar. The results show that this method can identify the propagation mode of elastic waves in the bar intuitively and clearly. The first three orders of propagation modes are stimulated in the bar 04, while only the first order of propagation is stimulated in the other eight bars. The local phase-amplitude joint correction algorithm can avoid correcting the component of the non-axial elastic wave. The rising edge of the average stress curve on the impact surface of bar 01 and bar 04 is corrected from 4.13 &mu, s and 4.09 &mu, s to 2.70 &mu, s, respectively.

Published
2020

13. Non-uniform illumination endoscopic imaging enhancement via anti-degraded model and L L -based variational retinex.

Author

Rao, Zhitao, Xu, Tingfa, Luo, Jiqiang, Guo, Jie, Shi, Guokai, and Wang, Hongqing

Subjects
RETINAL anatomy, ENDOSCOPY, ANALYSIS of variance, REFLECTANCE, COLOR image processing
Abstract

In this paper, we propose a novel image enhancement algorithm via anti-degraded model and L L -based variational retinex (AD- L L VR) for non-uniform illumination endoscopic images. Firstly, a haze-free endoscopic image is obtained by an anti-degraded model named dark channel prior (DCP). For getting a more accurate transmission map, it is refined by using a guided image filtering. Secondly, the haze-free endoscopic image is decomposed into detail and naturalness components by light filtering. Thirdly, a logarithmic Laplacian-based gamma correction (LLGC) is added to the naturalness component for preventing color cast and uneven lighting. Fourthly, we assume that the error between the detail component of the haze-free image and the product of associated reflectance and background illumination follows Gaussian-Laplacian distribution. So, the associated reflectance component can be obtained by using the proposed L L -based variational retinex ( L L VR) model. Finally, the recombination of modified naturalness component and associated reflectance component become the final result. Experimental results demonstrate that the proposed algorithm reveals more details in the background regions as well as other interesting areas and can mostly prevent the color cast. It has a better performance on increasing diagnosis and reducing misdiagnosis than other existing enhancement methods. [ABSTRACT FROM AUTHOR]

Published
2017
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results