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

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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Free Viewpoint Action Recognition based on Self-similarities

Free Viewpoint Action Recognition based on Self-similarities

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2012 IEEE 11th International Conference on Signal processing(ICSP 2012)

作者： Jiao Wang Changhong Chen Xiuchang Zhu Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781467321969

Action recognition is an important topic in computer vision and most current work focuses on view-dependent representations. In this paper, we develop a novel free viewpoint action recognition based on Self-similarity matrix (SSM), which tends to be stable across views. We choose Local Self-similarity (LSS) descriptor as our low-level feature, then SSM is calculated by computing the similarity between any pair of frame features. Each video sequence is represented using a diagonal descriptor vector extracted from the SSM. Support Vector Machines (SVM) is employed for classification. The encouraging experimental results on the public IXMAS multi-view data set demonstrate effectiveness of the proposed method.

关键词： local self-similarity descriptor self-similarity matrix diagonal feature action recognition view independent

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Video object matching based on sift algorithm

Video object matching based on sift algorithm

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2008 IEEE International Conference Neural Networks and Signal processing, ICNNSP

作者： Xuelong, Hu Yingcheng, Tang Zhenghua, Zhang School of Information Engineering Yangzhou University Yangzhou Jiangsu 225009 China Jiangsu Prov. Key Lab for Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing Jiangsu 210003 China Jiangsu Prov. Key Lab. for Computer Information Processing Technology Suzhou University Suzhou Jiangsu 215006 China

ISBN: (纸本)9781424423118

SIFT (Scale Invariant Feature Transform) is used to solve visual tracking problem, where the appearances of the tracked object and scene background change during tracking. The implementation of this algorithm has five major stages: scale-space extrema detection;keypoint localization;orientation assignment;keypoint descriptor;keypoint matching. From the beginning frame, object is selected as the template, its SIFT features are computed. Then in the following frames, the SIFT features are computed. Euclidean distance between the object's SIFT features and the frames' SIFT features can be used to compute the accurate position of the matched object. The experimental results on real video sequences demonstrate the effectiveness of this approach and show this algorithm is of higher robustness and real-time performance. It can solve the matching problem with translation, rotation and affine distortion between images. It plays an important role in video object tracking and video object retrieval. © 2008 IEEE.

关键词： Tracking (position)

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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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Improv.d SAI method using non-local spatial constraint for image interpolation

Improved SAI method using non-local spatial constraint for i...

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2011 International Conference on Wireless communications and Signal processing, WCSP 2011

作者： Bian, Jueping Gan, Zongliang Zhang, Mengcheng Zhu, Xiuchang Jiangsu Province Key Lab on Image Processing and Image Communication NUPT Nanjing China

ISBN: (纸本)9781457710100

This paper proposes an improv.d image interpolation method based on the soft-decision adaptive interpolation (SAI) algorithm. Natural images often contain repeatable patterns and structures throughout the image, which is called non-local property. We can use this non-local strategy to improv. the interpolation quality by better estimating the model parameters and Lagrangian multiplier. There are two steps in our method. In the first step, similar patches of the given block are found in the initialized high resolution image, and the model parameters can be determined properly using the expanded piecewise auto regression (PAR) model and non-local spatial constraint. In the second step, the self-similarity of patches across the high and low resolution images is exploited to solve the Lagrangian multiplier , thus to make the data estimation robust. Experiments indicate that the improv.d method can achieve good results both subjectively and objectively. © 2011 IEEE.

关键词： Interpolation

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Compressed Video Super-resolution Reconstruction Based on Regularized Algorithm

Compressed Video Super-resolution Reconstruction Based on Re...

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2006 8th International Conference on Signal processing

作者： Xu Zhong-qiang Gan Zongliang Zhu Xiu-chang Information Industry Ministry and Jiangsu Province Key Lab of Image Processing & Image Communication Nanjing University of Posts & Telecommunications

ISBN: (纸本)0780397371

Estimating high-resolution(HR) video from a sequence of low-resolution(LR) compressed observations is the focus of this *** on the theory of regularization,this paper proposes a new form of regularized cost function to control the within-channel balance between received data and prior information,and a channel weight coefficient to control the cross-channel *** LR frames are adaptively weighted according to their reliability and the regularization parameter is simultaneously estimated for each channel with ameliorating artifacts in compressed *** iterative gradient descent algorithm is utilized to reconstruction the HR *** results demonstrate that the proposed algorithm has an improv.ment in terms of both objective and subjective quality.

关键词： Regularization multichannel super-resolution reconstruction compressed video

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image retrieval based on bit-plane distribution feature

Image retrieval based on bit-plane distribution feature

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6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009

作者： Shan, Zhao Jing, Lui School of Computer Science and Technology Henan Polytechnic University Jiaozuo 454003 China Jiangsu Prov. Key Lab. on Image Processing and Image Communication Nanjing University of Posts and Communication Nanjing 210003 China

ISBN: (纸本)9780769537351

Based on the analysis of color histogram for image retrieval, a new descriptor, bit-plane distribution feature(BPDF), is proposed in this paper. The image is firstly divided into eight bit-planes. Meantime, the Gray code of bit-planes is used to avoid the effect of changes in the intensity values on bit-planes. Then, according to the distribution of each bit-plane, a feature vector is constructed by the first four significant planes which contain most of the structural information of the image. Finally, the Mahalanobis distance is adopted to measure the similarity because of the correlation between the concerned vectors after designing a correlation-weighted matrix. Comparisons are conducted between BPDF and other descriptors. Experimental results show that the proposed method prov.des more significantly retrieval results than the traditional ones. © 2009 IEEE.

关键词： image retrieval

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Stereo Matching based on Robust Likelihoods and MST Leveraged Smoothness Priors

Stereo Matching based on Robust Likelihoods and MST Leverage...

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2012 IEEE 11th International Conference on Signal processing(ICSP 2012)

作者： Tianliang Liu Liang Wang Xiuchang Zhu Jiangsu Provincial Key Lab of Image Processing and Image Communication College of Telecommunications and Information Engineering Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781467321969

This paper proposes a global stereo correspondence using robust matching likelihoods and minimum spanning tree （MST） leveraged smooth priors in a probabilistic graphical model framework. The matching likelihoods of the stereo correspondence can be robustly constructed as data term by aggregating initial matching costs from Weber local descriptors using an unsymmetrical guided filtering in a linear model. The disparity priors are devised as smooth term to characterize the smoothness constraints leveraged by the MST structure. The presented stereo approach prov.des an effective and efficient way to reflect robust visual dissimilarity and resolve local and regional discontinuities. Experiments demonstrate that the proposed global stereo matching method can produce piecewise smooth, accurate and dense disparity map, while removing effectively the visual ambiguity of the stereo matching problem.

关键词： stereo vision Markov random field Weber descriptor minimun spanning tree QPBO optimization

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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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Error concealment for stereoscopic images using boundary smooth degree

Error concealment for stereoscopic images using boundary smo...

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2009 15th Asia-Pacific Conference on communications, APCC 2009

作者： Tang, Guijin Zhu, Xiuchang Jiangsu Key Lab of Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

ISBN: (纸本)9781424447855

Error concealment can be regarded as a sort of error resilient coding techniques. This paper proposes a method to recover lost blocks in stereoscopic images. We first utilize the correlation to perform disparity estimation to match the corresponding blocks for lost ones. And then we calculate the boundary smooth degree (BSD) for each recovered block. If BSD exceeds the threshold, it means that the boundary is discontinuous which mainly results from high detailed blocks, edge blocks or occluded blocks. So we consider neighboring blocks' BSD and estimate the content of a lost block, and adaptively use different methods to conceal it. Experimental results show that the proposed algorithm can greatly improv. the subjective and objective quality of the reconstructed image. ©2009 IEEE.

关键词： Errors

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