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Learning Dual-Domain Calibration and Distance-Driven Correlation Filter:A Probabilistic Perspective for UAV Tracking

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Computers, Materials & Continua 2023年第12期77卷 3741-3764页

作者： Taiyu Yan Yuxin Cao Guoxia Xu Xiaoran Zhao Hu Zhu Lizhen Deng Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and TelecommunicationsNanjingChina School of Computer Science Qufu Normal UniversityQufuChina National Engineering Research Center of Communication and Network Technology Nanjing University of Posts and TelecommunicationsNanjingChina

Unmanned Aerial Vehicle(UAV)tracking has been possible because of the growth of intelligent information technology in smart cities,making it simple to gather data at any time by dynamically monitoring events,people,the environment,and other aspects in the *** traditional filter creates a model to address the boundary effect and time filter degradation issues in UAV tracking *** these methods ignore the loss of data integrity terms since they are overly dependent on numerous explicit previous regularization *** light of the aforementioned issues,this work suggests a dual-domain Jensen-Shannon divergence correlation filter(DJSCF)model address the probability-based distance measuring issue in the event of filter *** two-domain weighting matrix and JS divergence constraint are combined to lessen the impact of sample imbalance and *** new tracking models that are based on the perspectives of the actual probability filter distribution and observation probability filter distribution are proposed to translate the statistical distance in the online tracking model into response *** model is roughly transformed into a linear equality constraint issue in the iterative solution,which is then solved by the alternate direction multiplier method(ADMM).The usefulness and superiority of the suggested strategy have been shown by a vast number of experimental findings.

关键词： Dual-domain weighting distance measure correlation filter ADMM

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AMTrans:Auto-Correlation Multi-Head Attention Transformer for Infrared Spectral Deconvolution

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清华大学学报自然科学版（英文版） 2025年第3期30卷 1329-1341页

作者： Lei Gao Liyuan Cui Shuwen Chen Lizhen Deng Xiaokang Wang Xiaohong Yan Hu Zhu College of Electronic and Optical Engineering & College of Flexible Electronics(Future Technology) Nanjing University of Posts and TelecommunicationsNanjing 210003China Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and TelecommunicationsNanjing 210003China National Engineering Research Center of Communication and Network Technology Nanjing University of Posts and TelecommunicationsNanjing 210003China School of Computer Science and Technology Hainan UniversityHaikou 570228China

Infrared spectroscopy analysis has found widespread applications in various fields due to advancements in technology and industry *** improv. the quality and reliability of infrared spectroscopy signals,deconvolution is a crucial preprocessing *** by the transformer model,we propose an Auto-correlation Multi-head attention Transformer(AMTrans)for infrared spectrum sequence *** auto-correlation attention model improv.s the scaled dot-product attention in the *** utilizes attention mechanism for feature extraction and implements attention computation using the auto-correlation *** auto-correlation attention model is used to exploit the inherent sequence nature of spectral data and to effectively recovery spectra by capturing auto-correlation patterns in the *** proposed model is trained using supervised learning and demonstrates promising results in infrared spectroscopic *** comparing the experiments with other deconvolution techniques,the experimental results show that the method has excellent deconvolution performance and can effectively recover the texture details of the infrared spectrum.

关键词： spectroscopy spectral deconvolution transformer auto-correlation mechanism

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Flicker-Free Adaptive Enhancement for Infrared Video 13

Flicker-Free Adaptive Enhancement for Infrared Video

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13th International Conference on Wireless communications and Signal processing, WCSP 2021

作者： Wei, Caixia Gan, Zongliang Nanjing University of Posts and Telecommunications Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing China

ISBN: (纸本)9781665407854

Infrared videos often suffer from low contrast and insufficient texture. In order to improv. poor visual effect, a novel infrared video enhancement method is proposed, which contains intra-frame brightness enhancement and inter-frame brightness continuity adjustment. In intra-frame brightness enhancement, it has two steps including global contrast enhancement and local details enhancement. To global contrast enhancement, the processed image contrast by geometric distribution, and it is incorporated into an optimization problem with a sorted histogram of each frame to yield a modified histogram. To local details enhancement, after Retinex decomposition, the reflection component is magnified by boundary preserving filter, and this strategy can effectively suppress noise in relatively uniform regions. Furthermore, to maintain inter-frame brightness continuity, adaptive parameters are introduced through optical flow to control the combination ratio of geometric distribution histogram, in which the enhancement degree of each frame can be adjusted according to inter-frame similarity and the moving region are enhanced adaptively according to the change of each frame. Experimental results demonstrate that proposed algorithm can effectively enhance the contrast and detail of infrared video, and improv. the visual effect in subjective and objective quality evaluation. © 2021 IEEE.

关键词： Luminance

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Video smoke removal based on low-rank tensor completion via spatial-temporal continuity constraint

Video smoke removal based on low-rank tensor completion via ...

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作者： Zhu, Hu Xu, Guoxia Liu, Lu Deng, Lizhen Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and Telecommunication Nanjing China Department of Computer Science Norwegian University of Science and Technology Gjovik Norway National Engineering Research Center of Communication and Network Technology Nanjing University of Posts and Telecommunication Nanjing China

Smoke has a very bad effect on the outdoor vision system. Not only are the videos with poor visual effects obtained, but also the quality and structure of the videos are reduced. In this paper, we propose a video smoke removal method based on low-rank tensor completion via spatial-temporal continuity constraint. The proposed method is based on the smoke mixing model and consider the sparseness of smoke and the global and local consistency of clean video. Then, the optimal solution of the smoke removal algorithm model is quickly realized by the Alternating Direction Method of Multiplier. Finally, we evaluate the experiment results of real-world data and simulated data from the visual effects and objective indicators. And the experiment results show that our proposed algorithm can achieve better smoke removal results. © 2021 John Wiley & Sons, Ltd.

关键词： Smoke

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Retinex based flicker-free low-light video enhancement 1

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2nd Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2019

作者： Tu, Juanjuan Gan, Zongliang Liu, Feng Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing210003 China

ISBN: (数字)9783030317232

ISBN: (纸本)9783030317225

Videos captured in low light environment tend to be poor visual effect. To get better visual experience, a video enhancement algorithm based on improv.d center-surrounded Retinex and optical flow is proposed in this paper, which contains intra-frame brightness enhancement and inter-frame brightness continuity. In intra-frame brightness enhancement, reflection of each frame is estimated by adjusting the illumination using a weight factor, so that bright illumination is compressed to obtain a reflection with approximately uniform illumination. Then logarithmic image processing subtraction (LIPS) is adopted to enhance its contrast. To maintain inter-frame brightness continuity, the background and brightness changes of adjacent frames are measured using optical flow and just noticeable difference (JND) threshold, respectively. If the background and average brightness change little, their reflection brightness is almost the same, so LIPS parameter of previous frame is applied to current frame. Otherwise, current frame will be updated by calculating its own parameter. Experimental results demonstrate that proposed algorithm performs well in brightness continuity and detail enhancement. © Springer Nature Switzerland AG 2019.

关键词： Luminance

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Low-light image enhancement based on Retinex theory and dual-tree complex wavelet transform

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Optoelectronics Letters 2018年第6期14卷 470-475页

作者： YANG Mao-xiang TANG Gui-jin LIU Xiao-hua WANG Li-qian CUI Zi-guan LUO Su-huai Jiangsu Key Lab on Image Processing & Image Communication Nanjing University of Posts and Telecommunications School of Electrical Engineering and Computing University of NewcastleNSW 2308 Australia

In order to enhance the contrast of low-light images and reduce noise in them, we propose an image enhancement method based on Retinex theory and dual-tree complex wavelet transform(DT-CWT). The method first converts an image from the RGB color space to the HSV color space and decomposes the V-channel by dual-tree complex wavelet transform. Next, an improv.d local adaptive tone mapping method is applied to process the low frequency components of the image, and a soft threshold denoising algorithm is used to denoise the high frequency components of the image. Then, the V-channel is rebuilt and the contrast is adjusted using white balance method. Finally, the processed image is converted back into the RGB color space as the enhanced result. Experimental results show that the proposed method can effectively improv. the performance in terms of contrast enhancement, noise reduction and color reproduction.

关键词： Retinex theory dual-tree complex wavelet transform image enhancement

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Retinex based low-light image enhancement using guided filtering and variational framework

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Optoelectronics Letters 2018年第2期14卷 156-160页

作者：张诗唐贵进刘小花罗苏淮王大东 Jiangsu Key Lab on Image Processing & Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China School of Electrical Engineering and Computing The University of Newcastle NSW 2308 Australia CSIRO Data61 PO Box 76 Epping NSW 1710 Australia

A new image enhancement algorithm based on Retinex theory is proposed to solve the problem of bad visual effect of an image in low-light conditions. First, an image is converted from the RGB color space to the HSV color space to get the V channel. Next, the illuminations are respectively estimated by the guided filtering and the variational framework on the V channel and combined into a new illumination by average gradient. The new reflectance is calculated using V channel and the new illumination. Then a new V channel obtained by multiplying the new illumination and reflectance is processed with contrast limited adaptive histogram equalization(CLAHE). Finally, the new image in HSV space is converted back to RGB space to obtain the enhanced image. Experimental results show that the proposed method has better subjective quality and objective quality than existing methods.

关键词： RGB CLAHE Retinex based low-light image enhancement using guided filtering and variational framework HSV

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Anchored Neighborhoods Search Based on Global Dictionary Atoms for Face Photo-Sketch Synthesis

Anchored Neighborhoods Search Based on Global Dictionary Ato...

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2019第十一届数字图像处理国际会议

作者： Feng Liu Ran Xu Jieying Zheng Qiuli Lin Zongliang Gan College of Educational Science and Technology Nanjing University of Posts and Telecommunications Jiangsu Province Key Lab on Image Processing & Image Communications Nanjing University of Posts and Telecommunications Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications

Example-based face sketch synthesis technology generally requires face photo-sketch images with face alignment and size *** break through the limitation,we propose a global face sketch synthesis method:In training,all training photo-sketch patch pairs are collected together and a photo feature dictionary is learned from the photo *** each atom of the dictionary,its K closest photo-sketch patch pairs are clustered,namely "Anchored Neighborhood".In testing,for each test photo patch,we search its nearest photo patch in the Anchored Neighborhood determined by its closest atom,then the corresponding sketch patch is the *** the same way,we train and test in the high-frequency domain and synthesis the high-frequency ***,the fusion of the initial and the high-frequency results is the final *** experiments on three public face sketch datasets and various real-world photos demonstrate the effectiveness and robustness of the proposed method.

关键词： Face sketch synthesis Dictionary learning Dictionary atom Anchored neighborhood image patch

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Vehicle Color Recognition Based on Superpixel Features

Vehicle Color Recognition Based on Superpixel Features

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2019第十一届数字图像处理国际会议

作者： Qiuli Lin Feng Liu Qiang Zhao Ran Xu Jiangsu Province Key Lab on Image Processing & Image Communications Nanjing University of Posts and Telecommunications College of Educational Science and Technology Nanjing University of Posts and Telecommunications Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications

In this paper,a novel methodology is presented to settle the region of interest(ROI) detection problem in vehicle color recognition so as to remove the redundant components of vehicles that interfere greatly with color *** order to make full use of the local color and spatial information,vehicle images are divided into different superpixels at *** spatial relationship between superpixels and the outermost pixels is then used for the background removal of vehicle *** comparing with the vehicle window clustering centroids obtained by k-means,the superpixels close to the universal color characteristics of windows are removed so that the dominant color superpixels are ***,a linear Support Vector Machine classifier is trained for color *** experiments demonstrate that the proposed methodology is effective for color region of interest detection and thus contribute to vehicle color recognition.

关键词： vehicle color recognition region of interest superpixel universal color characteristics Support Vector Machine

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Pixel classified colourisation method based on neighbourhood similarity priori

Pixel classified colourisation method based on neighbourhood...

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作者： Chen, Jie Gan, Zongliang Zhu, Xiuchang Wang, Jin Jiangsu Province Key Lab on Image Processing and Image Communication Nanjing University of Post and Telecommunications P.O. Box 166 No. 66 Xin Mofan Road Nanjing Jiangsu China College of Information Engineering Yangzhou University No. 88 South University Ave Yangzhou Jiangsu China

Colourisation is a kind of computer-aided technology which automatically adds colours to greyscale images. This paper presents a scribble-based colourisation method which treats the flat and edge pixels differently. First, we classify the pixels to flat or edge pixel categories using the neighbourhood similarity pixels searching algorithm. Then, we compute the weighted coefficients of the edge pixels by solving a constraint quadratic programming problem and compute the weighted coefficients of the flat pixels based on their luminance distances. Finally, we transmit the weighted coefficients to the chrominance images according to the joint correlation property between luminance and chrominance channels, and combine with the colours scribbled on by the user to compute all the unknown colours. The experimental results show that our method is effective especially on reducing colour bleeding in the boundary parts and can give better results when only a few colours are scribbled on. © 2018 Inderscience Enterprises Ltd.

关键词： Quadratic programming

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