检索结果-内蒙古大学图书馆

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

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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Mixed image de-noising method of Bayesian estimation and wavelet based on alpha-stable distribution

Mixed image de-noising method of Bayesian estimation and wav...

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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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image interpolation based on decomposition

Image interpolation based on decomposition

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18th International Symposium on Intelligent Signal processing and communication Systems, ISPACS 2010

作者： Guo, Nana Song, Li Yang, Xiaokang Zhang, Wenjun Institute of Image Communication and Information Processing Shanghai Jiao Tong University Shanghai Key Lab. of Digital Media Processing and Transmission Shanghai 200240 China

ISBN: (纸本)9781424473717

This paper proposes a new approach for interpolating natural images. Unlike other conventional interpolation methods, we exploit the characteristics of an image and decompose it into a texture part and a non-texture (cartoon) part. In the non-texture part, we interpolate it with bicubic interpolation which performs well for smooth areas. We deal the texture part with peak transform based interpolation which resets the image pixels to capture the characters of the texture through peak transform. The experiment results demonstrate our new interpolation method has higher PSNR and better subjective quality of the interpolated image, especially in the texture part. © 2010 IEEE.

关键词： Interpolation

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Approaches to image retrieval using fuzzy set theory

Approaches to image retrieval using fuzzy set theory

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2008 IEEE International Conference Neural Networks and Signal processing, ICNNSP

作者： Li, Yang Xuelong, Hu Jun, Pan 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 Jiangsu Prov. Key Lab. for Computer Information Processing Technology Suzhou University Suzhou Jiangsu 215006 China

ISBN: (纸本)9781424423118

This paper mainly presents two approaches for image retrieval. There is some faintness in color locating in quantification boundary when image color is quantized. The membership function in fuzzy set theory can describe the fuzzy transition preferably. In this paper, the membership function in HSI color space is adopted to solve the problem above. At the same time, spatial information is integrated with color feature to describe the image content more truly. Due to the importance of texture feature, gray concurrence matrix is extracted. In the second part of this paper, retrieval scheme combining four image feature descriptors is presented, and then follows Fuzzy Hamming Distance (FHD) which is used as a fuzzy similarity measure. We have performed an experiment on a 1000 images database and our results show higher retrieval accuracy. © 2008 IEEE.

关键词： Fuzzy sets

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Content-based image retrieval using fuzzy hamming distance

Content-based image retrieval using fuzzy hamming distance

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2007 8th International Conference on Electronic Measurement and Instruments, ICEMI

作者： Hu, Xuelong Yang, Li Zhang, Gensheng School of Information Engineering Yangzhou University Yangzhou 225009 China Jiangsu Province Key Lab. for Image Processing and Communication Nanjing University of Post and Telecommunications Nanjing 215006 China Jiangsu Province Key Lab. for Computer Information Processing Technology Suzhou University Suzhou 215006 China

ISBN: (纸本)1424411351

This paper addresses an effective issue of content-based image retrieval (CBIR) by presenting Fuzzy Hamming Distance (FHD). Firstly, the theory of FHD is introduced, which includes degree of difference and cardinality of the fuzzy set, and then follows defuzzification of FHD which is used as a fuzzy similarity measure. In the experiment, the image retrieval results show this method can be employed to capture implicitly some semantic contents of the image in addition to other features such as color, texture and shape. Finally, an implemented prototype system demonstrates a promising retrieval performance for a test database, as compared with FUZZYCLUB system. © 2007 IEEE.

关键词： Hamming distance

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image fusion algorithm based on features motivated multi-channel pulse coupled neural networks

Image fusion algorithm based on features motivated multi-cha...

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2nd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2008

作者： Qu, Xiaobo Yan, Jingwen Dept. of Communication Engineering Xiamen University Fujian 361005 China Key Lab. of Digital Signal and Image Processing of Guangdong Province Shantou University Guangdong 515063 China

ISBN: (纸本)9781424417483

Pulse coupled neural networks (PCNN) is a mammal visual cortex-inspired artificial neural networks. Owing to the coupling links in neurons, PCNN is successful to utilize the local information, thus it has been successfully employed in image fusion. However, in traditional PCNN for image fusion, value of per pixel is used to motivate per neuron. In this paper, image feature of per pixel, e.g. gradient and local energy, is used to motivate per neuron and generate firing maps. Each firing map is corresponding to one type feature. Furthermore, a new multichannel PCNN is presented to combine these firing maps via a weighting function which measures the contribution of these features to the fused image quality. Finally, pixels with maximum firing times, when firing times of source images are compared, are selected as the pixels of the fused image. Experimental results demonstrate that the proposed algorithm outperforms Waveletbased and Wavelet-PCNN-based fusion algorithms. © 2008 IEEE.

关键词： image fusion

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A new method for semi-automatic image annotation

A new method for semi-automatic image annotation

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2007 8th International Conference on Electronic Measurement and Instruments, ICEMI

作者： Xuelong, Hu Yuhui, Zhang Li, Yang School of Information Engineering Yangzhou University Yangzhou 225009 China Jiangsu Province Key Lab. of Image Processing and Communication Nanjing University of Post and Telecommunications Nanjing 215006 China Jiangsu Province Key Lab. of Computer Information Processing Technology Suzhou University Suzhou 215006 China

ISBN: (纸本)1424411351

Semantic-based image retrieval bridges the gap between visual features and human understanding of image in the field of image retrieval. image annotation is one important technology of image retrieval based on the semantic. This paper proposed one method to realize semi-automatic image annotation with the tool Support Vector Machine (SVM). The image collection was divided into two parts, one for manual annotation and the other for testing. After being classified by SVM, the output was changed into a probability, and K-NN algorithm was applied to get the keywords for unlab.led images. The experiments show that the approach is feasible. © 2007 IEEE.

关键词： Support vector machines

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Efficient Rate Control Algorithm for Multi-view Video Coding

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China communications 2011年第3期8卷 83-89页

作者：刘峰熊婕范晶晶林琼洁 Image Processing & Image Communication Key Lab of Jiangsu Province Nanjing University of Posts and Telecommunications Key Lab of Broadband Wireless Communication and Sensor Network Technology(Nanjing University of Posts and Telecommunications) Ministry of Education

Rate control is one of the key factors influencing the multi-view video ***,there is not a rate control algorithm in the existing Joint Multi-view Video Coding *** this paper,an efficient rate control algorithm and a bit allocation strategy for multi-view video coding are *** order to obtain the consistent view quality,a bit allocation model based on the Lagrange optimum algorithm is firstly ***,considering the encoding statistical characteristics of different view types,a view weighting factor is introduced,and it will help improve the precision of bit allocation among *** with the fixed QP control strategy,experiment results show that the proposed algorithm can efficiently control the bit rate and obtain more consistent views,with video visual quality improved.

关键词： rate control rate distortion bit allocation view weighting factor

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image super-resolution based on sparse representation and nonlocal regularization

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Journal of Computational Information Systems 2014年第5期10卷 2107-2116页

作者： Li, Xin Zhu, Xiuchang Jiangsu Province Key Lab. on Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

To solve the super-resolution reconstruction problem for single-frame image, an algorithm based on sparse representation and nonlocal regularization is proposed. By training the joint dictionaries, this algorithm looks for sparse representation in low-resolution dictionary for the input low-resolution image patch, and maps the sparse representation to high-resolution dictionary to construct high-resolution image patch. Then the reconstructed image patch is further regularized by the image's nonlocal self-similarity a priori information. Experimental results show that this algorithm can effectively ensure the quality of the reconstructed image, and greatly reduce the computation time. © 2014 Binary Information Press.

关键词： image reconstruction

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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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