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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 *** improve 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 improves 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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An efficient fast inter mode decision algorithm for h.264/avc ***

An efficient fast inter mode decision algorithm for h.264/av...

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2009 WRI International Conference on communications and Mobile Computing, CMC 2009

作者： Huang, Huaibin Hu, Dong Key Lab. of Image Processing and Image Communications of Jiangsu Province Nanjing University of Posts and Telecom Nanjing 210003 China

ISBN: (纸本)9780769535012

An efficient fast inter mode decision algorithm for the baseline H.264/AVC video coding is proposed in this paper. The main idea of the algorithm is to reduce the number of candidate modes for Rate Distortion Optimization(RDO) by using early mode detection in four different levels, viz. SKIP mode detection, type detection at macroblock-level, type detection at submacroblock-level and intra modes detection. In addition, the correlation of cost of current MB and the one of previous frame, as well as the cost's monotonous property are both used to help the mode decision. Compared to JM8.6 reference software, our algorithm can save encoding time 71.743% on average with negligible PSNR loss, which is very helpful for H.264/AVC inter frame encoding. © 2009 IEEE.

关键词： Electric distortion

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Partical swarm optimization based unequal loss protection of embedded video streams

Partical swarm optimization based unequal loss protection of...

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2010 IEEE 12th International Conference on Communication Technology, ICCT'2010

作者： Hu, Jiajing Hu, Dong Key Lab. of Image Processing and Image Communications of Jiangsu Province Nanjing University of Posts and Telecom Nanjing 210003 China

ISBN: (纸本)9781424468690

This paper presents a new scheme for optimal packetization of scalab.e multimedia data over lossy network. By assigning an unequal amount of forward error correction (FEC) bits to each segment of transmission packets, the proposed algorithm protects a progressive bitstream generated by a three-dimensional set partitioning in hierarchical trees (3-D SPIHT) algorithm. The partical swarm optimization (PSO) algorithm is used to reasonably allocate bits between source coding and channel coding across packets. Experimental results show that the proposed algorithm provides close to optimal average peak signal-to-noise ratio performance and that its'running time is significantly lower than that of previously known solution. © 2010 IEEE.

关键词： Signal to noise ratio

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Robust license plate detection through auxiliary information and context fusion model 2nd

Robust license plate detection through auxiliary information...

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

作者： Wang, Ning Liu, Feng Gan, Zongliang Jiangsu Province Key Lab on Image Processing and Image Communications Nanjing University of Posts and Telecommunications Nanjing210003 China

ISBN: (纸本)9783030317256

License plate detection has wide applications in the intelligent transportation system, while it still remains challenges to improve the robustness under various shooting distance and observation angles. To get better performance, a novel convolutional-neural-network-based method is proposed, which is achieved with auxiliary information and context fusion model. First, the auxiliary information is employed in our framework, which corresponds with resolutions, orientations and shapes of license plates. Specifically, the multiple resolutions are collected through integrating multi-level features of convolution hierarchy. Besides the various scales and ratios, the region proposal network RPN with multi-angle anchors and branching structure is applied to generate proper proposals. Second, an effective context fusion model is designed to fully exploit the hidden correlation between license plates and contextual properties. The local and contextual features are independently learned in the dual pathways, which are later joint to form a powerful representation in subsequent layers. Comprehensive experiments on the publicly availab.e datasets confirm the effectiveness of the proposed method. © Springer Nature Switzerland AG 2019.

关键词： Convolution

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Liver Tumor Segmentation Based on Three-Channel Cascaded SEU-Nets and C-LSTM 13

Liver Tumor Segmentation Based on Three-Channel Cascaded SEU...

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

作者： Li, Yarong Hu, Dong Nanjing University of Posts and Telecommunications Jiangsu Province's Key Lab of Image Processing and Image Communications Nanjing China

ISBN: (纸本)9781665407854

An abdominal CT liver tumor segmentation algorithm based on three-channel cascade SEU-Nets and C-LSTM is proposed in this paper. Concerning the accuracy of most known algorithms is limited by using single-phase CT images, the proposed method takes advantage of the different characteristics of the lesion area in the venous phase, arterial phase and delayed phase, and the correlation between slices in enhanced CT images. It uses three-channel SEU-Nets as the encoder to extract image features of slices in three phases, and uses 3D convolution to extract the relationship between slices for the same location at different phases. And then it uses C-LSTM to extract the inter-slice sequence feature relationship. Finally, the decoder outputs fine segmentation of liver tumor output. 40 sets of high-quality abdominal-enhanced CT images of the liver and liver tumors used in the experiment were collected in the provincial central hospital and annotated by experts. Comparisons are carried out with well-known methods, such as improved CFCNs, H-DenseUNet network and DBAs-based multi-scale DC-CUNets segmentation network. Experimental results show that the average segmentation accuracy of proposed algorithm is 7.04% higher than that of the multi-scale DC-CUNets segmentation network based on DBAs, and the DICE coefficient is improved by 4.89%. © 2021 IEEE.

关键词： Long short-term memory

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Unequal loss protection of embedded streams combining particle swarm optimization and local search

Unequal loss protection of embedded streams combining partic...

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International Conference on Multimedia and Signal processing

作者： Hu, Jiajing Hu, Dong Key Lab of Image Processing and Image Communications of Jiangsu Province Nanjing University of Posts and Telecom Nanjing 210003 China

ISBN: (纸本)9780769543567

FEC-based multiple description coding (MDC) is an effective method for the transmission of scalab.e video stream over noisy network. However, given the transmission bandwith, it's time-consuming to find the optimal packet number and packet length as well as reasonably allocate bits between source coding and channel coding across the packets. In this paper, we state the optimal unequal error protection(UEP) as a two-level optimization problem and use a rate-optimal solution in initial step of searching. Then, we propose a new scheme, which combines the particle swarm optimization (PSO) with the local search(LS) algorithms, so that optimal solution can be found in more efficient way. Experimental results for the 3D set partitioning in hierarchical trees (SPIHT) coders show that the new algorithm provides close to optimal average peak signal-to-noise ratio performance and that its' running time is obviously lower than that of previously known algorithms.© 2011 IEEE.

关键词： Particle swarm optimization (PSO)

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Improved 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 improved 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 improve 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 improved 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 improvement in terms of both objective and subjective quality.

关键词： Regularization multichannel super-resolution reconstruction compressed video

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Optimal approximation of head-related transfor function based on adaptive genetic algorithm

Optimal approximation of head-related transfor function base...

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2008 IEEE International Conference Neural Networks and Signal processing, ICNNSP

作者： Xuelong, Hu Yan, Tang Jun, Cai School of Information Engineering Yangzhou University Yangzhou Jiangsu 225009 China Jiangsu Province Key Lab. for Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing Jiangsu 210003 China

ISBN: (纸本)9781424423118

Head-related Transfer Functions (HRTFs) refer to the spectral filtering from sound sources to listeners' eardrums or ear canals. As an effective model structure, the degree of the IIR filter approximation of the HRTFs, whose design and implementation is a specific spectrum function approximation process, is much lower than that of the FIR. Based on the assessment of HRTFs different importance for sound sources recognition in different spectrum bands, and associated with some perspectives of psychoacoustics in spatial hearing, adaptive and revalued coding genetic algorithm (GA) is applied to the approximation of the HRTFs zero-pole model. The results show that, on an average, the performance of adaptive GA is better than that of the traditional GA. ©2008 IEEE.

关键词： Transfer functions

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A NOVEL ALGORITHM OF SUPER-RESOLUTION RECONSTRUCTION FOR COMPRESSED VIDEO

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Journal of Electronics(China) 2007年第3期24卷 363-368页

作者： Xu Zhongqiang Zhu Xiuchang Information Industry Ministry and Jiangsu Province Key Lab of Image Processing ＆ Image Communication Nanjing University of Posts ＆ Telecommunications Nanjing 210003 China

Super-Resolution (SR) technique means to reconstruct High-Resolution (HR) images from a sequence of Low-Resolution (LR) observations,which has been a great focus for compressed video. Based on the theory of Projection Onto Convex Set (POCS),this paper constructs Quantization Constraint Set (QCS) using the quantization information extracted from the video bit stream. By combining the statistical properties of image and the Human Visual System (HVS),a novel Adaptive Quantization Constraint Set (AQCS) is proposed. Simulation results show that AQCS-based SR al-gorithm converges at a fast rate and obtains better performance in both objective and subjective quality,which is applicable for compressed video.

关键词： Super-Resolution (SR) Compressed video Projection Onto Convex Set (POCS) Quantization Constraint Set (QCS)

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