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2008 IEEE International Conference Neural Networks and Signal processing, ICNNSP

作者： Zhijian, Wang Xuelong, Hu Cheng, Li Liping, Wang 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 Yangzhou Jiangsu 225001 China

ISBN: (纸本)9781424423118

This paper introduces a new kind of recovery method which is the combination of Bayesian estimation and wavelet threshold. Wavelet coefficients of signals show strong characteristics of the non-Gauss statistics, its probability density function can be modeled by alpha-stable priori distribution. This paper uses Bayesian estimation to obtain the low frequency coefficients, and deals with high frequency coefficients with the wavelet soft threshold, then restore signal by wavelet inverse transform. Bayesian estimation well retains the marginal information of signals, but the signal is still not very smooth recovery and wavelet soft threshold can maintain smooth characteristic. The mixed noise elimination methods of Bayesian estimation and wavelet enhance the peak SNR much greater than wavelet threshold, which has better recovery effect. ©2008 IEEE.

关键词： Probability density function

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Contour extraction model introducing contrast adaptive characteristics based on visual pathway

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Multimedia Tools and Applications 2024年第15期84卷 14693-14717页

作者： Fang, Tao Cai, Zhefei Fan, Yingle College of Electronics and Information Hangzhou Dianzi University Hangzhou310018 China Zhejiang Provincial Key Laboratory of Information Processing Communication and Networking Hangzhou310027 China Laboratory of Pattern Recognition and Image Processing Hangzhou Dianzi University Hangzhou310018 China

Effectively extracting image subject contours holds significant importance for subsequent image processing tasks. Recognizing the pivotal role of contrast features in contour characterization, this paper proposes a novel contour extraction model with contrast adaptive characteristics, inspired by visual perception simulation visual pathways. Firstly, leveraging the color antagonism traits of retinal ganglion cells, we construct a color image contrast calculation model to enhance the representation of visual information contrast. Furthermore, drawing upon the feed-forward impact of the retina on Lateral Geniculate Nucleus (LGN) cells, we introduce a contrast gain control mechanism to extract multi-directional primary contour responses. Secondly, employing the LIF neuron network to simulate the lateral geniculate body's information flow processing mechanism, we encode visual information via pulse firing to eliminate redundant contour details. Then, by considering the primary visual cortex (V1) cell's receptive field size variation with contrast, we devise a contrast-adaptive dynamic receptive field model. Additionally, we develop a texture suppression model based on the orientation/contrast disparity between the receptive field model's center and periphery. Finally, integrating the primary contour response and the image obtained through the inhibition model, we fuse features to derive the final image subject target contour. This study employs the BSDS500 dataset and the RuG40 dataset for experimentation. Comparative analysis against mainstream methods demonstrates our approach's superior ability to retain the main image outline while suppressing non-edge textures, with P-value indicators for contour detection of 0.58 and 0.50, respectively. Furthermore, visual analysis using box and whisker plots confirms the robustness of our proposed method. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Textures

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A NOVEL METHOD TO REALIZE COMPRESSED VIDEO SUPER-RESOLUTION RECONSTRUCTION

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Journal of Electronics(China) 2006年第2期23卷 310-313页

作者： Zhou Liang Liu Feng Zhu Xiuchang Information Industry Ministry and Jiangsu Province Key Lab of lmage Processing and Image Communication Nanjing University of Posts and Communications Nanjing 210003 China

This letter proposes a novel method of compressed video super-resolution reconstruction based on MAP-POCS (Maximum Posterior Probability-Projection Onto Convex Set). At first assuming the high-resolution model subject to Poisson-Markov distribution, then constructing the projecting convex based on MAP. According to the characteristics of compressed video, two different convexes are constructed based on integrating the inter-frame and intra-frame information in the wavelet-domain. The results of the experiment demonstrate that the new method not only outperforms the traditional algorithms on the aspects of PSNR (Peak Signal-to-Noise Ratio), MSE (Mean Square Error) and reconstruction vision effect, but also has the advantages of rapid convergence and easy extension.

关键词： Super-resolution Compressed video image reconstruction MAP-POCS

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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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Adaptive double-buffered rate smoothing method for scalable network transmission of stereo video

Adaptive double-buffered rate smoothing method for scalable ...

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2010 International Conference on Audio, Language and image processing, ICALIP 2010

作者： Gu, Feng Sun, Jun Zhou, Jun Institute of Image Communication and Information Processing Shanghai Jiaotong University Shanghai Key Laboratory of Digital Media Processing and Transmissions 200240 Shanghai China

ISBN: (纸本)9781424458653

We study on the transmission of stereo videos over network. Because stereoscopic displays do not come into wide use, we need to separate the stereo video depending on the classification of views to satisfy different terminal displays when we transport the video over network. This transporting method of stereo video in Internet is called the view scalable transmission [1]. But there comes one question, the rate jitter of different views will become much larger in this transmitting method. So in this paper, we propose an adaptive double-buffered rate smoothing method to solve the problem. Experiment results validate our studies on the effects of dealing with rate jitter. ©2010 IEEE.

关键词： Jitter

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Appearance model based moving object matching across disjoint camera views

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2nd International Conference on Opto-Electronics Engineering and Materials Research, OEMR 2013

作者： Yu, Kong Shuai Hu, Dong Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology The key lab of image processing and image communications of Jiangsu Province Nanjing University of Posts and Telecom Nanjing 210003 China

ISBN: (纸本)9783037857731

A new object tracking scheme for multi-camera surveillance with non-overlapping views is proposed in this paper. Brightness transfer function (BTF) is used to establish relative appearance correspondence between different views. Mixtures of probabilistic principal component analysis (MPPCA) is incooperated to learn the subspace of brightness transfer function with the concern to deal with multiple different brightness areas in a scene. The incremental major color spectrum histogram (IMCSH) is used as similarity measure for reliable matching. Experimental results with real world videos show the effectiveness of the proposed algorithm. © (2013) Trans Tech Publications, Switzerland.

关键词： Luminance

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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 provides more significantly retrieval results than the traditional ones. © 2009 IEEE.

关键词： image retrieval

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A Novel Method to Get Super-Resolution images from Low-Resolution Compressed Video

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The Journal of China Universities of Posts and Telecommunications 2005年第2期12卷 50-54页

作者： ZHOU Liang ZHU Xiu-chang Information Industry Ministry and Jiangsu Province Key Lab of Image Processing and Image Communication Nanjing University of Posts and Communications Nanjing 210003 P. R. China

In order to resolve the problems of discontented restoration effect and confined applying scope which exist in the current compressed video restoration algorithms, a novel method to get super-resolution images from low-resolution compressed video is proposed in this paper. At first, a uniform model is presented and the restoration problem in the Bayesian framework is formulated under the MAP criterion, then the focus is put on the hybrid motion-compensation and transform coding schemes, at last the methods of getting the parameters are provided. The results of the simulation clearly demonstrate that our method not only has the properties of finer vision effect and wider applying scope, but also performs better than those of current classical algorithms in the aspects of Peak Signal Noise Ratio （PSNR） under the basis of the same condition.

关键词： super-resolutlon compressed video restoration

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Re-ranking image search results by multiscale visual saliency model

Re-ranking image search results by multiscale visual salienc...

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2010 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, BMSB 2010

作者： Huang, Jun Yang, Xiaokang Zhang, Rui Fang, Xiangzhong Institute of Image Communication and Information Processing Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9781424444625

The paper focuses on two mechanisms, multiscale relevance and visual saliency, in web image search. First, in most current web image search engines, such as Google image Search, Yahoo image Search and so on, people judge the relevance of search results by the thumbnails and then click through the thumbnails to check if the corresponding image is really relevant. Basically the thumbnail and the corresponding image give the multiscale representations of the image. The second is that from visual point of view, it is obvious that salient images would be easier to catch users' eyes and more likely to be clicked than cluttered ones in low-level vision. In this paper, we build a multiscale saliency model and apply it to re-rank the results from web image search engines. Experimental results show that the model can achieve an average precision (AP) [1] of as high as 97%, and it improves the results of Google image search significantly.

关键词： Search engines

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Restoration-enhanced reversible information steganography network for CT images in the Internet of Medical Things

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IEEE Transactions on Instrumentation and Measurement 2025年

作者： Chen, Kai Chen, Yang Coatrieux, Gouenou Wu, Jiasong Coatrieux, Jean-Louis School of Cyber Science and Engineering Southeast University Nanjing210096 China Southeast University Nanjing210096 China IMT Atlantique Inserm LaTIM UMR1101 Brest29000 France Laboratoire Traitement du Signal et de L'Image Université de Rennes 1 RennesF-35000 France Centre de Recherche en Information Biomédicale Sino-francais Rennes35042 France National Institute for Health and Medical Research RennesF-35000 France Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing School of Computer Science and Engineering Southeast University Nanjing210096 China Jiangsu Key Laboratory of Molecular and Functional Imaging Department of Radiology Zhongda Hospital Southeast University Nanjing210009 China Ministry of Education Nanjing210096 China Ministry of Education Nanjing210096 China

Smart health and emotional care powered by the Internet of Medical Things (IoMT) are revolutionizing the healthcare industry by adopting several technologies related to multimodal physiological data collection, communication, intelligent automation, and efficient manufacturing. The security of medical images containing private patient information distributed in IoMT is of paramount importance in social communication, and guaranteeing their reliability has attracted widespread attention. Some existing medical image steganography methods fail to guarantee the original image's integrity, authenticity, and lossless restoration. To solve this problem, a restoration-enhanced reversible adaptive information steganography network, MediSR-Net, is proposed. Specifically, MediSR-Net consists of an analysis module and an encoding module. The image degradation-restoration strategy is exploited by the analysis module to improve the effectiveness of information embedding and perceptual field to reduce the error of pixel prediction. An information distillation and attention machine-based approach are adopted to achieve degradation-restoration of CT medical images at any scale and focus more on the degradation-restoration effect with small magnification factors. The encoding module is responsible for the embedding and extraction of privacy information. Ten state-of-the-art are compared with the MediSR-Net method concerning steganographic effect, embedding rate, distortion analysis, and prediction error. The qualitative and quantitative results demonstrate the effectiveness and superiority of MediSR-Net. © 1963-2012 IEEE.

关键词： Steganography

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