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2007 IEEE International Conference on Image Processing最新文献

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Hierarchical Tensor Approximation of Multidimensional Images 多维图像的层次张量逼近
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4379951
Qing Wu, Tian Xia, Yizhou Yu
{"title":"Hierarchical Tensor Approximation of Multidimensional Images","authors":"Qing Wu, Tian Xia, Yizhou Yu","doi":"10.1109/ICIP.2007.4379951","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4379951","url":null,"abstract":"Visual data comprises of multi-scale and inhomogeneous signals. In this paper, we exploit these characteristics and develop an adaptive data approximation technique based on a hierarchical tensor-based transformation. In this technique, an original multi-dimensional image is transformed into a hierarchy of signals to expose its multi-scale structures. The signal at each level of the hierarchy is further divided into a number of smaller tensors to expose its spatially inhomogeneous structures. These smaller tensors are further transformed and pruned using a collective tensor approximation technique. Experimental results indicate that our technique can achieve higher compression ratios than existing functional approximation methods, including wavelet transforms, wavelet packet transforms and single-level tensor approximation.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116379607","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: 17
Estimation of Fade and Dissolve Parameters for Weighted Prediction in H.264/AVC H.264/AVC中加权预测中衰落和溶解参数的估计
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4379821
Fatih Kamisli, D. Baylon
{"title":"Estimation of Fade and Dissolve Parameters for Weighted Prediction in H.264/AVC","authors":"Fatih Kamisli, D. Baylon","doi":"10.1109/ICIP.2007.4379821","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4379821","url":null,"abstract":"Weighted prediction (WP) is one way of overcoming the limitations of simple motion compensation for scenes with gradual transitions such as fades or dissolves. In WP, the predictions for inter coded blocks are obtained from scaled versions of the reference frames. H.264/AVC is the first video coding standard that has incorporated WP tools. In this paper, we focus on the estimation of weights for WP in dissolves. Our findings indicate that the estimation approaches for dissolves should be different from the estimation approaches for fades. Specifically, estimating the weights jointly for the two reference frames of B-frames gives better performance for dissolves under most circumstances.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":"178 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116578055","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
Nonconvex Regularization for Shape Preservation 形状保持的非凸正则化
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4378949
R. Chartrand
{"title":"Nonconvex Regularization for Shape Preservation","authors":"R. Chartrand","doi":"10.1109/ICIP.2007.4378949","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4378949","url":null,"abstract":"We show that using a nonconvex penalty term to regularize image reconstruction can substantially improve the preservation of object shapes. The commonly-used total-variation regularization, int |nablau|, penalizes the length of object edges. We show that int |nablau|p, 0 < p < 1, only penalizes edges of dimension at least 2 - p, and thus finite-length edges not at all. We give numerical examples showing the resulting improvement in shape preservation.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122293457","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: 42
A New Scheme for Automatic Initialization of Deformable Models 一种可变形模型自动初始化的新方案
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4380011
Weijia Shen, A. Kassim
{"title":"A New Scheme for Automatic Initialization of Deformable Models","authors":"Weijia Shen, A. Kassim","doi":"10.1109/ICIP.2007.4380011","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4380011","url":null,"abstract":"This paper presents a novel scheme for automatic initialization for all types of deformable models. Our method is able to automatically generate a close-to-boundary initialization which is independent of the subsequent segmentation process. Therefore, our method enables different types of deformable models achieve more accurate and robust results. Topographic independent component analysis (TICA) based feature extraction technique is presented for learning a representation from a set of un-labeled image patches. During learning, a topographic map of basis components emerge. An intelligent contour generation procedure is also proposed. Experimental results on abdominal CT images demonstrate the potential of our approach.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122491859","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: 6
A Video Watermarking Based on 3-D Complex Wavelet 基于三维复小波的视频水印
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4379873
Jingwei Wang, Xinbo Gao, J. Zhong
{"title":"A Video Watermarking Based on 3-D Complex Wavelet","authors":"Jingwei Wang, Xinbo Gao, J. Zhong","doi":"10.1109/ICIP.2007.4379873","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4379873","url":null,"abstract":"A video watermarking embedding and detection algorithm is proposed in complex wavelet transform (CWT) domain. The host video sequence is firstly segmented into shots. Then each shot is projected onto 3D CWT domain. To achieve robustness while keeping imperceptibility, a perceptual mask derived from 3D complex wavelet coefficients is introduced to weight the watermarks and the results is added back to the complex wavelet coefficients. Finally the inverse 3D CWT is applied to obtain the watermarked video shots. The experimental results illustrate that the proposed algorithm has more advantages in remaining video qualities while keeping the same resistance to attacks over that in discrete wavelet transform (DWT) domain.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122554023","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: 8
Automatic Recognition of Partial Shoeprints Based on Phase-Only Correlation 基于相位相关性的部分鞋印自动识别
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4380049
M. Gueham, A. Bouridane, D. Crookes
{"title":"Automatic Recognition of Partial Shoeprints Based on Phase-Only Correlation","authors":"M. Gueham, A. Bouridane, D. Crookes","doi":"10.1109/ICIP.2007.4380049","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4380049","url":null,"abstract":"In this paper, a method for automatically recognizing partial shoeprint images for use in forensic science is presented. The technique uses the phase-only correlation (POC) for shoeprints matching. The main advantage of this method is its capability to match low quality shoeprint images accurately and efficiently. In order to achieve superior performance, the use of a spectral weighting function is also proposed. Experiments were conducted on a database of images of 100 different shoes available on the market. For experimental evaluation, test images including different perturbations such as noise addition, blurring and textured background addition were generated. Results have shown that the proposed method is very practical and provides high performance when processing low quality partial-prints. The use of a weighting function provides an improvement in the recognition rate in particularly difficult cases.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122606875","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: 48
PCA-Based Image Registration : Application to On-Line MR Temperature Monitoring of Moving Tissues 基于pca的图像配准在运动组织核磁共振温度在线监测中的应用
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4379266
G. Maclair, B. D. Senneville, M. Ries, B. Quesson, P. Desbarats, J. Benois-Pineau, C. Moonen
{"title":"PCA-Based Image Registration : Application to On-Line MR Temperature Monitoring of Moving Tissues","authors":"G. Maclair, B. D. Senneville, M. Ries, B. Quesson, P. Desbarats, J. Benois-Pineau, C. Moonen","doi":"10.1109/ICIP.2007.4379266","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4379266","url":null,"abstract":"Real-time magnetic resonance (MR) thermometry provides continuous temperature mapping inside the human body and is therefore a promising tool to monitor and control interventional therapies based on thermal ablation. Temperature information must be mapped to a reference position of observed organs in order to allow thermal dose computation, as the history of temperature is required for each pixel. Motion compensated MR-thermometry for thermotherapy has to cope with radio-frequency (RF) artifacts and relaxation-time changes of the monitored tissue. While purely optical-flow-based realignment may lead to temperature map computation errors for the case of local or global intensity changes, principal component analysis based realignment results in accurately registered temperature maps. The motion estimation process described in this paper consists of two steps : a parameterized flow models is initially computed using a principal component analysis during a preparative learning step; during the intervention, motion is characterized with a small set of parameters using a least square solver.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122908423","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: 7
Fast Computation of Inverse Krawtchouk Moment Transform using Clenshaw's Recurrence Formula 用克伦肖递推公式快速计算克劳tchouk矩逆变换
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4379948
P. A. Raj, V. Appala
{"title":"Fast Computation of Inverse Krawtchouk Moment Transform using Clenshaw's Recurrence Formula","authors":"P. A. Raj, V. Appala","doi":"10.1109/ICIP.2007.4379948","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4379948","url":null,"abstract":"This paper proposes a method for fast computation of inverse Krawtchouk moment transform for signal and image reconstruction using Clenshaw's recurrence formula. It is shown that the proposed approach requires lesser computations than the straightforward method of computation for signal and image reconstruction. In order to verify the proposed approach, simulation results are reported for 1D signal and 2D image reconstructions from the given Krawtchouk moments for signal and image. The proposed approach is suitable for parallel VLSI implementation because the proposed structure is simple, regular and modular.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122223829","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: 11
Enabling Better Medical Image Classification Through Secure Collaboration 通过安全协作实现更好的医学图像分类
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4380054
Jaideep Vaidya, Bhakti Tulpule
{"title":"Enabling Better Medical Image Classification Through Secure Collaboration","authors":"Jaideep Vaidya, Bhakti Tulpule","doi":"10.1109/ICIP.2007.4380054","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4380054","url":null,"abstract":"Privacy is of growing concern in today's day and age. Protecting the privacy of health data is of paramount importance. With the rapid advancement in imaging technology, analysis of medical images is now one of the most dynamic fields of study today. Image analysis is performed for a variety of purposes, ranging from image enhancement to image segmentation. It can easily be seen that having access to more information makes the analysis results more accurate. For example, supervised classification based image segmentation requires good and plentiful training data. We wish to utilize the training data at different locations to obtain more accurate image segmentation while still protecting the privacy of individual patients. Work in the field of secure multi-party computation (SMC) in cryptography shows how to compute functions securely and quantifies what it means to be secure. Applying SMC protocols in image processing is a challenging problem. This paper looks at how some of this work can be leveraged to perform privacy-preserving image analysis and classification.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116883093","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: 3
Geometric Features Based Framework for Colonic Polyp Detection using a New Color Coding Scheme 基于几何特征的彩色编码结肠息肉检测框架
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4379753
Dongqing Chen, A. Farag, M. Hassouna, R. Falk, G. Dryden
{"title":"Geometric Features Based Framework for Colonic Polyp Detection using a New Color Coding Scheme","authors":"Dongqing Chen, A. Farag, M. Hassouna, R. Falk, G. Dryden","doi":"10.1109/ICIP.2007.4379753","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4379753","url":null,"abstract":"Curvature-based geometric features have been proven to be important for colonic polyp detection. In this paper, we present an automatic detection framework and color coding scheme to highlight the detected polyps. The key idea is to place the detected polyps at the same locations in a newly created polygonal dataset with the same topology and geometry properties as the triangulated mesh surface of real colon dataset, and assign different colors to the two separated datasets to highlight the polyps. Finally, we validate the proposed framework by computer simulated and real colon datasets. For fifteen synthetic polyps with different shapes and different sizes, the sensitivity is 100%, and false positive is 0. For four real colon datasets, the proposed algorithm has achieved the sensitivity of 75%.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117026298","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: 14
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