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Efficient Rate Control Algorithm for Multi-view Video Coding

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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A camera self-calibration method based on dual constraints of multi-view images

A camera self-calibration method based on dual constraints o...

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

作者： Liu, Feng Han, Weiwei Xu, Qiong Lin, Qiongjie Fan, Jingjing Image Processing and Image Communication Jiangsu Key Laboratory Nanjing China Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781457710100

Camera calibration is the essential step of obtaining 3D information from 2D views in the field of computer vision, which is widely used in the area of 3D reconstruction, navigation, visual supervision, etc. A camera self-calibration method based on dual constraints of multi-view images is proposed to make calibration possible when there is no reference calibration block or the movement of camera is arbitrary. In this method, multi-view images are preprocessed first to select three images which are most suitable for camera self-calibration, then we use the method based on the genetic algorithm, the camera parameters are finally estimated by using epipolar geometry matching error and reprojection error as fitness functions as two steps. Experimental results show that the proposed camera self-calibration method is correct and effective. © 2011 IEEE.

关键词： Genetic algorithms

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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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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年无线通信与信号处理国际会议(WCSP 2011)

作者： Jueping Bian Zongliang Gan Mengcheng Zhang Xiuchang Zhu Jiangsu province key lab on image processing & image communication NUPT Nanjing China

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 λ, thus to make the data estimation robust. Experiments indicate that the improved method can achieve good results both subjectively and objectively.

关键词： image interpolation the SAI algorithm non-local self-similarity

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Super-resolution based on two dictionary-pairs

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Sensors and Transducers 2013年第10期157卷 289-294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

For learning-based super-resolution reconstruction, the selection and training of dictionary play an important role in improving image reconstruction quality. A super-resolution algorithm based on two dictionary-pairs is proposed in this paper. This algorithm selects image's high- and mid-frequency components as the features of high- and low-resolution patches respectively, and gets the first dictionary-pair, i.e. joint-basic high/low-resolution dictionary-pair, by means of joint training. Then it calculates the difference between original high/mid-frequency components and reconstructed high/mid-frequency components with the first dictionary-pair, and composes the second dictionary-pair, i.e. residual high- and low-resolution dictionary-pair. During super-resolution reconstruction, the high-frequency component and residual high-frequency component of low-resolution image are reconstructed respectively with the above two dictionary-pairs. The experiment results show that, the subjective and objective reconstruction quality could be effectively improved by our proposed algorithm. © 2013 IFSA.

关键词： image reconstruction

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A camera self-calibration method based on dual constraints of multi-view images

A camera self-calibration method based on dual constraints o...

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2011年无线通信与信号处理国际会议(WCSP 2011)

作者： Feng Liu Weiwei Han Qiong Xu Jingjing Fan Qiongjie Lin Image Processing and Image Communication Jiangsu Key Laboratory Key Lab of Broadband Wireless Commun Image Processing and Image Communication Jiangsu Key Laboratory

关键词： multi-view images camera calibration dual constraints genetic algorithm epipolar geometry reprojection error

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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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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 novel spatial information recovery algorithm based on fuzzy clustering in H.264

A novel spatial information recovery algorithm based on fuzz...

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IEEE International Symposium on Intelligent Signal processing and communication Systems (ISPACS)

作者： Han Shen Xiu-chang Zhu Jiangsu Province Key Lab on Image Processing & Image Communication Nanjing University of Posts and Telecommunications China

As no reference frame can be obtained in Intra-frame error concealment, reducing the degradation of spatial reconstructed image is one of the key techniques in error concealment. In this paper, a novel spatial error concealment algorithm based on fuzzy clustering for Intra-frame in H.264 is proposed. This proposed algorithm gives a new selection of eigenvectors and similarity measurement for fuzzy clustering. The experimental results show that the proposed algorithm can improve the edge details, achieve a better subjective quality of the recovered image and increase PSNR (Peak Signal-to-Noise Ratio) as well.

关键词： Clustering algorithms Signal processing algorithms image reconstruction Degradation PSNR Resilience Video sequences Frequency Discrete cosine transforms Fuzzy systems

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Adaptive resampling in particle filter based on diversity measures

Adaptive resampling in particle filter based on diversity me...

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International Conference on Computer Science and Education

作者： Yu, Jin-Xia Liu, Wen-Jing Tang, Yong-Li College of Computer Science and Technology Henan Polytechnic University Jiaozuo 454003 China Jiangsu Provincial Key Lab. of Image Processing and Image Communication Nanjing University of Posts and Communication Nanjing 210003 China Department of Computer Science and Technology Tsinghua University Beijing 100084 China

ISBN: (纸本)9781424460052

It is very important to find a criterion when to perform a resampling step. Aimed at this problem, an adaptive resampling algorithm in particle filter based on diversity measures is presented. Based on the analysis and comparison of two diversity measures that are effective sample size (ESS) and population diversity factor(PDF), the resampling algorithm based on ESS is introduced. On the basis of that, PDF is used for adaptively tuning the resampling threshold. At last, with the simulation program using matlab.7.0 to track a single target motion from a fixed visual observation points, the performance of the proposed algorithm is evaluated and its validity is verified. ©2010 IEEE.

关键词： MATlab

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