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2011 Sixth International Conference on Image and Graphics最新文献

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Image Interpolation Using Autoregressive Model and Gauss-Seidel Optimization 基于自回归模型和高斯-塞德尔优化的图像插值
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.155
Ketan Tang, O. Au, Lu Fang, Zhiding Yu, Yuanfang Guo
{"title":"Image Interpolation Using Autoregressive Model and Gauss-Seidel Optimization","authors":"Ketan Tang, O. Au, Lu Fang, Zhiding Yu, Yuanfang Guo","doi":"10.1109/ICIG.2011.155","DOIUrl":"https://doi.org/10.1109/ICIG.2011.155","url":null,"abstract":"In this paper we propose a simple yet effective image interpolation algorithm based on autoregressive model. Unlike existing algorithms which rely on low resolution pixels to estimate interpolation coefficients, we optimize the interpolation coefficients and high resolution pixel values jointly from one optimization problem. Although the two sets of variables are coupled in the cost function, the problem can be effectively solved using Gauss-Seidel method. We prove the iterations are guaranteed to converge. Experiments show that on average we have over 3dB gain compared to bicubic interpolation and over 0.1dB gain compared to SAI.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122164419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 15
Low Bit Rate Compression for SAR Image Based on Blocks Reordering and 3D Wavelet Transform 基于块重排序和三维小波变换的SAR图像低比特率压缩
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.21
Yuan Chen, Rong Zhang
{"title":"Low Bit Rate Compression for SAR Image Based on Blocks Reordering and 3D Wavelet Transform","authors":"Yuan Chen, Rong Zhang","doi":"10.1109/ICIG.2011.21","DOIUrl":"https://doi.org/10.1109/ICIG.2011.21","url":null,"abstract":"Due to that there are a large number of similar characteristics in surface structure of the SAR image, a novel SAR image compression algorithm was proposed based on 3D wavelet transform after block reordering. This proposed algorithm consists of four successive steps: divide the image into sub-blocks with equal size, reorder the sub-blocks according to the similarity measured by weighted Euclidean distance to form 3D array, then 3D wavelet transform and 3D-SPIHT coding are employed for encoding. Experimental results of real SAR images show that the proposed method outperforms the traditional wavelet-based SPIHT in terms of PSNR, especially at the low-bit rate.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125430285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
An Efficient Authorship Protection Scheme for Shared Multimedia Content 一种有效的共享多媒体内容著作权保护方案
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.183
Mohamed El-Hadedy, Georgios Pitsilis, S. J. Knapskog
{"title":"An Efficient Authorship Protection Scheme for Shared Multimedia Content","authors":"Mohamed El-Hadedy, Georgios Pitsilis, S. J. Knapskog","doi":"10.1109/ICIG.2011.183","DOIUrl":"https://doi.org/10.1109/ICIG.2011.183","url":null,"abstract":"Many electronic content providers today like Flickr and Google, offer space to users to publish their electronic media(e.g. photos and videos) in their cloud infrastructures so that they can be publicly accessed. Features like including other information, such as keywords or owner information into the digital material is already offered by existing providers. Despite the useful features made available to users by such infrastructures, the authorship of the published content is not protected against various attacks such as compression. In this paper we propose a robust scheme that uses digital invisible watermarking and hashing to protect the authorship of the digital content and provide resistance against malicious manipulation of multimedia content. The scheme is enhanced by an algorithm called MMBEC, that is an extension of an established scheme MBEC towards higher resistance.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125578486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Fast Pedestrian Detection with Laser and Image Data Fusion 激光与图像数据融合快速行人检测
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.107
Bo Wu, Jixiang Liang, Qixiang Ye, Zhenjun Han, Jianbin Jiao
{"title":"Fast Pedestrian Detection with Laser and Image Data Fusion","authors":"Bo Wu, Jixiang Liang, Qixiang Ye, Zhenjun Han, Jianbin Jiao","doi":"10.1109/ICIG.2011.107","DOIUrl":"https://doi.org/10.1109/ICIG.2011.107","url":null,"abstract":"In this paper, we proposed a pedestrian detection system based on laser and image data fusion. The high speed of laser data based location and precise of image based classification are fully explored. First, laser scanner point data is clustered into segments, each of which implies a pedestrian candidate. Then, the segments are projected to the image domain to form regions of interest (ROI) on the image, given camera calibration parameters. Finally two SVM classifiers on Histogram of Oriented Gradient (HOG) features are used to precisely locate pedestrians on the ROI. Experiments report over 30 times higher speed than the state-of-the-art method and a comparable detection rate.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125865956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 13
QR Iterative Subspace Identification and Its Application in Image Denoising QR迭代子空间识别及其在图像去噪中的应用
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.176
Chanzi Liu, Qingchun Chen
{"title":"QR Iterative Subspace Identification and Its Application in Image Denoising","authors":"Chanzi Liu, Qingchun Chen","doi":"10.1109/ICIG.2011.176","DOIUrl":"https://doi.org/10.1109/ICIG.2011.176","url":null,"abstract":"The foundation of compressed sensing (CS) is the sparse representation of signals. Over-complete dictionaries could be utilized to map signals into their sparse representation over the dictionary. And iterative subspace identification (ISI) is an effective algorithm to determine the over-complete dictionary from signal samples. In this paper, the QR decomposition is proposed to be employed in the ISI scheme so as to obtain the adaptive over-complete dictionary. It is shown that the QR-ISI outperforms the ISI in terms of the recovered PSNR. Finally, the QR-ISI method could be applied to image denoising. Experiment results are presented to show that the QR-ISI offers a feasible method for image denoising with reasonable performance.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127399511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Bag-of-Features Based Classification of Breast Parenchymal Tissue in the Mammogram via Jointly Selecting and Weighting Visual Words 基于特征袋的视觉词联合选择加权乳腺实质组织分类
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.192
Jingyan Wang, Yongping Li, Y. Zhang, Honglan Xie, Chao Wang
{"title":"Bag-of-Features Based Classification of Breast Parenchymal Tissue in the Mammogram via Jointly Selecting and Weighting Visual Words","authors":"Jingyan Wang, Yongping Li, Y. Zhang, Honglan Xie, Chao Wang","doi":"10.1109/ICIG.2011.192","DOIUrl":"https://doi.org/10.1109/ICIG.2011.192","url":null,"abstract":"Automatically classifying the tissues types of region of interest (ROI) in medical imaging has been a important application in computer-aided diagnosis, such as classification of breast parenchymal tissue in the mammogram. Recently, bag-of-features method has show its power in this field, treating each medical image as a set of local features. In this paper, we investigate using the bag-of-features strategy to classify the tissue types in medical imaging applications. Two important issues are considered here: the visual vocabulary learning and weighting. Although there are already plenty of algorithms to deal with them, all of them treat them independently, namely, the vocabulary learned first and then the histogram weighted. Inspired by Auto-Context who learns the features and classier jointly, we try to develop a novel algorithm who learns the vocabulary and weights jointly. The new algorithm, called Joint-ViVo, works in a iterative way. In each iteration, we first learn the weights for each visual word by maximizing the margin of ROI triplets, and then based on the learned weights, we select the most discriminate visual words for the next iteration. We test our algorithm by classifying breast tissue density in mammograms. The results show that Joint-ViVo can perform effectively for classifying tissues and support the idea that vocabulary should be learned jointly with the weights.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130794920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 28
Learning Based Adaptive Denoising Approach for Image Interpolation 基于学习的图像插值自适应去噪方法
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.89
Z. Gan, L. Qi, Xiuchang Zhu
{"title":"Learning Based Adaptive Denoising Approach for Image Interpolation","authors":"Z. Gan, L. Qi, Xiuchang Zhu","doi":"10.1109/ICIG.2011.89","DOIUrl":"https://doi.org/10.1109/ICIG.2011.89","url":null,"abstract":"In this paper, we propose an effective image interpolation framework through learning based adaptive denoisng approach. In the local area, error pattern between original image and interpolated image is treated as stationary Gaussian distribution. Under the initial estimation, the proposed method apply the patch as the basic unit, in which Multiclass SVM classifier is used to determine iteration number and denoise parameters. There are two steps in iterative processing, including adaptive denoise and data fusion. Experiment results shown the proposed method can significantly improve the interpolated image quality both subjectively and objectively.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132364088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
GPU Based Implementation of 3DTV System 基于GPU的3DTV系统实现
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.68
Lianghao Wang, J. Zhang, Shao-Jun Yao, Dongxiao Li, Ming Zhang
{"title":"GPU Based Implementation of 3DTV System","authors":"Lianghao Wang, J. Zhang, Shao-Jun Yao, Dongxiao Li, Ming Zhang","doi":"10.1109/ICIG.2011.68","DOIUrl":"https://doi.org/10.1109/ICIG.2011.68","url":null,"abstract":"This paper focuses on the near real-time implementation of end-to-end 3DTV System. It is specially designed for the generation of high-quality disparity map and depth-image-based rendering (DIBR) on the graphics processing unit (GPU) through CUDA (Compute Unified Device Architecture) API. We propose our novel methods including a kind of stereo matching with adaptive windows and an asymmetric edge adaptive filter (AEAF) for industrial application. These algorithms are structured in a way that exposes as much data parallelism as possible and the power of shared memory and data parallel programming in GPU is exploited. We evaluate our proposed methods and implementation based on the benchmark Middlebury and the experiment results show that our method is suitable for application on the trade-off among accuracy and execution speed. Running on an NVIDIA Quadro FX4800 graphics card, for each 480x375 stereo images with 60 disparity levels, the proposed system reaches about 146ms for stereo matching and reaches the speed of DIBR 5.7ms for rendering 1 view or 14ms for rendering 8 views.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134528190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
A Change Detection Method for Man-Made Objects in SAR Images Based on Curvelet and Level Set 基于曲线波和水平集的SAR图像中人造目标变化检测方法
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.80
Juan Su, Renming Wang, Kai Du
{"title":"A Change Detection Method for Man-Made Objects in SAR Images Based on Curvelet and Level Set","authors":"Juan Su, Renming Wang, Kai Du","doi":"10.1109/ICIG.2011.80","DOIUrl":"https://doi.org/10.1109/ICIG.2011.80","url":null,"abstract":"An unsupervised change detection method for man-made objects in co registered multi-temporal SAR images is proposed in this paper. Based on analyzing the edge structure property of man-made objects, the Curve let transform is used to denoise and enhance the difference image by manipulating certain Curve let coefficients. Then, the enhanced difference image is segmented into the changed and unchanged regions by level set method. Some prior knowledge of man-made objects in SAR images is exploited in both steps. The proposed method can overcome the drawbacks of traditional pixel-level change detection methods, and obtain robust detection results even for high level speckle noise. Experimental results demonstrate its effectiveness and feasibility.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123936211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
ContextRank: Personalized Tourism Recommendation by Exploiting Context Information of Geotagged Web Photos contextank:利用网络照片地理标记的语境信息进行个性化旅游推荐
2011 Sixth International Conference on Image and Graphics Pub Date : 2011-08-12 DOI: 10.1109/ICIG.2011.48
Kai Jiang, Peng Wang, Nenghai Yu
{"title":"ContextRank: Personalized Tourism Recommendation by Exploiting Context Information of Geotagged Web Photos","authors":"Kai Jiang, Peng Wang, Nenghai Yu","doi":"10.1109/ICIG.2011.48","DOIUrl":"https://doi.org/10.1109/ICIG.2011.48","url":null,"abstract":"In this paper, we propose a method: Context Rank, which utilizes the vast quantity of geo tagged photos in photo sharing website to recommend travel locations. To enhance the personalized recommendation performance, our method exploits different context information of photos, such as textual tags, geo tags, visual information, and user similarity. Context Rank first detects landmarks from photos' GPS locations, and estimates the popularity of each landmark. Within each landmark, representative photos and tags are extracted. Furthermore, Context Rank calculates the user similarity based on users' travel history. When a user's geo tagged photos are given, the landmark popularity, representative photos and tags, and the user similarity are used to predict the user preference of a landmark from different aspects. Finally a learning to rank algorithm is introduced to combine different preference predictions to give the final recommendation. Experiments performed on a dataset collected from Panoramio show that the Context Rank can obtain a better result than the state-of-the-art method.","PeriodicalId":277974,"journal":{"name":"2011 Sixth International Conference on Image and Graphics","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121193065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 21
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