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image Quality Assessment Based on Local Edge Direction Histogram

Image Quality Assessment Based on Local Edge Direction Histo...

2011 International Conference on image Analysis and Signal processing(2011第三届图像分析与信号处理国际会议 IASP 2011)

作者： Xiaolin Chen Rui Zhang Shibao Zheng Institute of Image Communication and Information Processing Department of Electronic EngineeringShanghai Key Laboratory of Digital Media Processing and TransmissionsShanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9781612848792

In this paper, we propose a new edge direction histogram (EDH) based on a structural similarity method for image quality assessment. We were motivated by the fact that the structural information of image can be described by the distribution of gradient magnitudes, as well as the one of edge directions. Therefore, we introduce the edge direction histogram to robustly represent the distribution of edge magnitudes and directions simultaneously. We further develop a distance metric to evaluate the quality of images by computing the structural similarity between EDH descriptors of the reference and the distorted one. Experimental results show that the proposed method outperforms some wellknown full-reference image quality metrics.

关键词： image quality assessment edge direction histogram structural similarity

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Robust restoration of low-dose cerebral perfusion CT images using NCS-Unet

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Nuclear Science and Techniques 2022年第3期33卷 62-76页

作者： Kai Chen Li-Bo Zhang Jia-Shun Liu Yuan Gao Zhan Wu Hai-Chen Zhu Chang-Ping Du Xiao-Li Mai Chun-Feng Yang Yang Chen Southeast University Nanjing 210096China School of Cyber Science and Engineering Southeast UniversityNanjing 210096China Key Laboratory of Computer Network and Information Integration(Southeast University) Ministry of EducationNanjing 210096China Department of Radiology General Hospital of the Northern Theater of the Chinese People’s Liberation ArmyShenyang 110016China Laboratory of Image Science and Technology The School of Computer Science and EngineeringSoutheast UniversityNanjing 210096China Department of Radiology Nanjing Drum Tower HospitalThe Affiliated Hospital of Nanjing University Medical SchoolNanjing 210008China Jiangsu Key Laboratory of Molecular and Functional Imaging Department of RadiologyZhongda HospitalSoutheast UniversityNanjing 210009China Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing School of Computer Science and EngineeringSoutheast UniversityNanjing 210096China

Cerebral perfusion computed tomography(PCT)is an important imaging modality for evaluating cerebrovascular diseases and stroke *** widespread public concern about the potential cancer risks and health hazards associated with cumulative radiation exposure in PCT imaging,considerable research has been conducted to reduce the radiation dose in X-ray-based brain perfusion *** the dose of X-rays causes severe noise and artifacts in PCT *** solve this problem,we propose a deep learning method called *** exceptional characteristics of non-subsampled contourlet transform(NSCT)and the Sobel filter are introduced into *** decomposes the convolved features into high-and low-frequency *** decomposed high-frequency component retains image edges,contrast imaging traces,and noise,whereas the low-frequency component retains the main image *** Sobel filter extracts the contours of the original image and the imaging traces caused by the contrast agent *** extracted information is added to NCS-Unet to improve its performance in noise reduction and artifact *** and quantitative analyses demonstrated that the proposed NCS-Unet can improve the quality of low-dose cone-beam CT perfusion reconstruction images and the accuracy of perfusion parameter calculations.

关键词： Cerebral perfusion CT Low-dose image denoising Perfusion parameters

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Data-consistent Unsupervised Diffusion Model for Metal Artifact Reduction

Data-consistent Unsupervised Diffusion Model for Metal Artif...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Tong, Zhan Wu, Zhan Yang, Yang Mao, Weilong Wang, Shijie Li, Yinsheng Chen, Yang Southeast University Laboratory of Image Science and Technology Nanjing210096 China Southeast University Ministry of Education Key Laboratory of Computer Network and Information Integration Nanjing210096 China Chinese Academy of Sciences Research Center for Medical Artificial Intelligence Shenzhen Institutes of Advanced Technology Shenzhen518055 China School of Computer Science and Engineering Key Lab. of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing The Laboratory of Image Science and Technology Nanjing210096 China

ISBN: (纸本)9798350337488

Computed Tomography (CT) is an imaging technique widely used in clinical diagnosis. However, high-attenuation metallic implants result in the obstruction of low-energy Xrays and further lead to metal artifacts in the reconstructed CT images. Deep supervised model-based metal artifact reduction(MAR) approaches are limited in clinical applications due to the difficulty in obtaining paired artifact-affected and artifactfree data. Furthermore, these model-based methods lack the consideration of data consistency in the sinogram-domain to perform exact metal trace inpainting. To address these challenges, we propose a Data-consistent unsupErVised diffusiOn model for meTal artifact rEDuction, called DEVOTED-Net. First, DEVOTED-Net leverages prior knowledge to guide the conditional diffusion model for fine-grained metal trace inpainting. Second, an unsupervised MAR framework is designed in the reverse process for the unknown metal traces restoration in the sinogram domain. Third, to further enhance the sinogram-domain data consistency, physics-based consistency constraint loss including conjugateray consistency loss and accumulation-ray consistency loss is designed. Extensive experiments are carried out to verify the performance of our algorithm on the publicly available dataset and clinical experimental dataset. This efficient, accurate, and reliable MAR approach holds great potential in clinics. © 2023 IEEE.

关键词： computed tomography deep unsupervised learning denoising diffusion probabilistic model Metal artifact reduction physics-based consistency constraint

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Performance improved method for pixel-domain Wyner-Ziv video coding system

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2007年第10期35卷 2014-2018页

作者： Gan, Zong-Liang Qi, Li-Na Zhu, Xiu-Chang Image Processing and Image Communication Key Laboratory Nanjing University of Posts and Telecommunications Nanjing 210003 China

Distributed video coding (DVC) is a new video compression paradigm based on two key information theories: Slepi-an-Wolf and Wyner-Ziv theorems, and it has the advantage of very lightweight encoder, high compression efficiency and inbuilt robustness. In this paper, pixel-domain Wyner-Ziv video algorithm, which is a typical DVC scheme, is analyzed at first. Then a performance improved method for pixel-domain Wyner-Ziv video coding system is presented. The proposed method, without sacrificing the encoder complexity, can calculate high quality side information using bi-directional motion estimation and reconstruct decoding frames using side information by joint iteration function based on Huber-Markov random field. Simulation results show that a better visual quality and 2dB average gain of Power Signal-to-Noise Ratio (PSNR) can be achieved with the proposed method at the decoder.

关键词： Signal encoding

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Joint multi-task cascade for instance segmentation

Joint multi-task cascade for instance segmentation

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作者： Wen, Yaole Hu, Fuyuan Ren, Jinchang Shang, Xinru Li, Linyan Xi, Xuefeng School of Electronic & Information Engineering Suzhou University of Science and Technology SuzhouJiangsu215009 China Centre for Signal and Image Processing University of Strathclyde Glasgow United Kingdom Suzhou Institute of Trade & Commerce SuzhouJiangsu215009 China Virtual Reality Key Laboratory of Intelligent Interaction and Application Technology of Suzhou Suzhou University of Science and Technology SuzhouJiangsu215009 China Suzhou Key Laboratory for Big Data and Information Service Suzhou University of Science and Technology SuzhouJiangsu215009 China

Instance segmentation requires both pixel-level classification accuracy and high-level semantic features at the target instance level, which is very challenging, and the cascade structure can effectively improve both of these problems. To make full use of the relationship between detection and segmentation, this paper proposes a joint multi-tasking cascade structure, which is not simply to cascade the two tasks of detection and segmentation, but to unitedly put them into multi-stage processing, and especially to integrate the information at different stages of the mask branch. The entire structure can effectively utilize the superior characteristics of each stage in the matter of detection and segmentation, thus improving the quality of mask prediction. The feature fusion process is introduced in the full convolution networks (FCN) branch, and the high-level and low-level features are effectively fused to enhance the contextual information of the picture semantic features. The experiments demonstrate the better results on the COCO dataset. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Semantics

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Design of three-dimensional gesture recognition and motion tracking human-computer intelligent interaction system based on PAJ7620

Design of three-dimensional gesture recognition and motion t...

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2021 International Conference on Information Technology and Intelligent Control, CITIC 2021

作者： Wang, Jian-Liang Wei, Ye Li, Yang Meng, Yuan Li, Ming-Yu Xu, Jiang-Yan Jiao, Wan-Ming Ban, Lan Liu, Jun-Pei Zhang, Hong-Feng Zhang, Wei Wang, Li-Na Luo, Fu-Chen Wang, Yu-Duo Tianjin College University of Science and Technology Beijing Tianjin China Civil Aviation University of China Tianjin Key Laboratory of Intelligent Signal and Image Processing Tianjin China Tianjin Normal University Tianjin Key Laboratory of Wireless Mobile Communication and Radio Energy Transmission Tianjin China Binhai College Nankai University Tianjin China Tianjin Tianshi College Tianjin China

With the increasing degree of informatization and intelligence in modern society, human-computer interaction technology has become one of the commonly used scientific and technological achievements. "Gesture" can be used as inputing image information, and make more intuitive and convenient for perception of user interface. To a certain extent, it can complete the intelligent interaction function between human and computer. The design is a human-computer intelligent interaction system for 3D gesture recognition and motion tracking based on gesture sensor PAJ7620. STM32 chip is used as the main control unit to recognize accurately, analyze and process different gestures collected by the gesture sensor, and control the OLED screen to display the gesture information. It can further drive the carrier to take corresponding actions and realize the intelligent human-computer interaction recognition of gestures. The experimental test results show that the recognition rate is lose to 100% when the distance is within 10cm. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Gesture recognition

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Multi-focus image Fusion Algorithm Based on Regional Firing Characteristic of Pulse Coupled Neural Networks

Multi-focus Image Fusion Algorithm Based on Regional Firing ...

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International Conference on Bio-Inspired Computing: Theories and Applications, BICTA

作者： Xiaobo Qu Jingwen Yan Department of Communication Engineering Xiamen University Xiamen China Key Laboratory of Digital Signal and Image Processing of Guangdong Province Shantou University Shantou China

Multi-focus image fusion aims at overcoming imaging cameras' finite depth of field by combining information from multiple images with the same scene. In this paper, a regional firing intensity (RFI) is defined, which is based on the statistical characteristic in local window of neuron firing times when pulse coupled neural networks (PCNN) is utilized in the image fusion. A novel image fusion algorithm based on regional firing characteristic PCNN (RFC-PCNN) is proposed and RFI is considered as a determination to select the coefficients of source images. First, a multiscale decomposition on each source image is performed by discrete wavelet transform. Second, PCNN is employed to extract features of source images in wavelet domain. Thirdly, RFI is computed and used to combine the coefficients of source images. Finally, the fused coefficients are used to reconstruct the fused image by an inverse discrete wavelet transform. Experimental results show that the proposed algorithm outperforms the wavelet-based and wavelet-PCNN-based fusion algorithms.

关键词： image fusion Neural networks Discrete wavelet transforms Radiofrequency interference Cameras Layout Neurons Feature extraction Wavelet domain image reconstruction

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Motion compensation optimization of H.264 decoder based on DSP hardware platform

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Nanjing Youdian Daxue Xuebao (Ziran Kexue Ban)/Journal of Nanjing University of Posts and Telecommunications (Natural Science) 2007年第2期27卷 80-84页

作者： Gan, Zong-Liang Wang, Kai Zhu, Xiu-Chang Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

The H.264 video coding standard has a significant performance benefit versus former standards. However, motion compensation decoding process takes up a significant decoding time due to the advanced coding features. In this paper, the theory of motion compensation decoding in H.264 is given at first. Then the improved method is proposed by motion compensation fast decoding algorithm and optimization based on ADI Blackfin533 hardware platform. Both PC and ADI Blackfin533 experimental results show that the proposed optimization strategy can substantially improve the efficiency of real-time H.264 decoder.

关键词： Digital signal processor Direct memory access H.264 Motion compensation decoding

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An Iterative Interference Cancellation Approach for OFDMA Uplink System

An Iterative Interference Cancellation Approach for OFDMA Up...

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WRI International Conference on communications and Mobile Computing, CMC

作者： Ruiqin Miao Jun Sun Lin Gui Jian Xiong Institute of Image Communication and Information Processing Shanghai Jiaotong University Shanghai China China and Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiaotong University Shanghai China

ISBN: (纸本)9781424463275;9780769539898

In this paper, the issue of carrier frequency offset compensation in orthogonal frequency division multiple access (OFDMA) uplink system is investigated. To mitigate the effect of the multiple access interference (MAI) caused by the carrier frequency offset (CFO) of different users, a new iterative compensation algorithm is proposed. However, this scheme has unaffordable complexity. To tackle this problem, an efficient iterative implementation is developed in this paper based on a banded interference matrix approximation. Simulations illustrate that the proposed algorithm obtains good performance, at the same time has much lower computational complexity.

关键词： Iterative methods Interference cancellation Multiple access interference Iterative algorithms Signal processing algorithms Frequency conversion OFDM Feedback Downlink Mobile communication

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A visual comfort metric for stereoscopic 3D video based on SMDE approach

A visual comfort metric for stereoscopic 3D video based on S...

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IEEE International Conference on Signal processing, communications and Computing (ICSPCC)

作者： Bi Ye Jun Zhou Institute of Image Communication and Information Processing Shanghai Jiao Tong University 200240 China Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiao Tong University Shanghai China

Visual comfort assessment for stereoscopic video is playing an important role for stereoscopic safety issue. In this paper, we propose a novel visual comfort assessment metric that utilizes interest regions detection approach, which is called Salient Motion Depth Extraction approach in our algorithm. In stereoscopic video shots, salient motion regions where human subjects focus on should have more weights in visual comfort assessment. To achieve better performance, our approach combines salient cues, motion cues with depth cues in order to extract salient motion regions in consideration of depth context. Our visual comfort assessment utilizes local analytical method based on attention model by analyzing disparity features in interest regions extracted by Salient Motion Depth Extraction approach. The experimental results have demonstrated that our proposed visual comfort assessment improves the correlation with the subjective assessment.

关键词： Visualization Context Measurement Feature extraction Humans Stereo image processing Computational modeling

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