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2007 IEEE International Conference on Image Processing最新文献

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Block-Based Gradient Domain High Dynamic Range Compression Design for Real-Time Applications 实时应用的基于块的梯度域高动态范围压缩设计
2007 IEEE International Conference on Image Processing Pub Date : 2007-12-12 DOI: 10.1109/ICIP.2007.4403041
Tsun-Hsien Wang, Wei-Ming Ke, Ding-Chuang Zwao, F. Chen, C. Chiu
{"title":"Block-Based Gradient Domain High Dynamic Range Compression Design for Real-Time Applications","authors":"Tsun-Hsien Wang, Wei-Ming Ke, Ding-Chuang Zwao, F. Chen, C. Chiu","doi":"10.1109/ICIP.2007.4403041","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4403041","url":null,"abstract":"Due to progress in high dynamic range (HDR) capture technologies, the HDR image or video display on conventional LCD devices has become an important topic. Many tone mapping algorithms are proposed for rendering HDR images on conventional displays, but intensive computation time makes them impractical for video applications. In this paper, we present a real-time block-based gradient domain HDR compression for image or video applications. The gradient domain HDR compression is selected as our tone mapping scheme for its ability to compress and preserve details. We divide one HDR image/frame into several equal blocks and process each by the modified gradient domain HDR compression. The gradients of smaller magnitudes are attenuated less in each block to maintain local contrast and thus expose details. By solving the Poisson equation on the attenuated gradient field block by block, we are able to reconstruct a low dynamic range image. A real-time Discrete Sine Transform (DST) architecture is proposed and developed to solve the Poisson equation. Our synthesis results show that our DST Poisson solver can run at 50 MHz clock and consume area of 9 mm2 under TSMC 0.18 um technology.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115615316","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: 16
Graph-Cut Rate Distortion Algorithm for Contourlet-Based Image Compression 基于contourlet的图像压缩图切率失真算法
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4379273
M. Trocan, B. Pesquet-Popescu, J. Fowler
{"title":"Graph-Cut Rate Distortion Algorithm for Contourlet-Based Image Compression","authors":"M. Trocan, B. Pesquet-Popescu, J. Fowler","doi":"10.1109/ICIP.2007.4379273","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4379273","url":null,"abstract":"The geometric features of images, such as edges, are difficult to represent. When a redundant transform is used for their extraction, the compression challenge is even more difficult. In this paper we present a new rate-distortion optimization algorithm based on graph theory that can encode efficiently the coefficients of a critically sampled, non-orthogonal or even redundant transform, like the contourlet decomposition. The basic idea is to construct a specialized graph such that its minimum cut minimizes the energy functional. We propose to apply this technique for rate-distortion Lagrangian optimization in subband image coding. The method yields good compression results compared to the state-of-art JPEG2000 codec, as well as a general improvement in visual quality.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114971504","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
Attack LSB Matching Steganography by Counting Alteration Rate of the Number of Neighbourhood Gray Levels 利用邻域灰度值变化率攻击LSB匹配隐写
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4378976
Fangjun Huang, Bin Li, Jiwu Huang
{"title":"Attack LSB Matching Steganography by Counting Alteration Rate of the Number of Neighbourhood Gray Levels","authors":"Fangjun Huang, Bin Li, Jiwu Huang","doi":"10.1109/ICIP.2007.4378976","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4378976","url":null,"abstract":"In this paper, we propose a new method for attacking the LSB (least significant bit) matching based steganography. Different from the LSB substitution, the least two or more significant bit-planes of the cover image would be changed during the embedding in LSB matching steganography and thus the pairs of values do not exist in stego image. In our proposed method, we get an image by combining the least two significant bit-planes and divide it into 3x3 overlapped subimages. The subimages are grouped into four types, i.e. T 1,T 2, T 3 and T 4 according to the count of gray levels. Via embedding a random sequence by LSB matching and then computing the alteration rate of the number of elements in T 1, we find that normally the alteration rate is higher in cover image than in the corresponding stego image. This new finding is used as the discrimination rule in our method. Experimental results demonstrate that the proposed algorithm is efficient to detect the LSB matching stegonagraphy on uncompressed gray scale images.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115396309","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: 63
Automatic Measures for Predicting Performance in Off-Line Signature 离线签名性能预测的自动度量方法
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4378968
F. Alonso-Fernandez, M. Fairhurst, Julian Fierrez, J. Ortega-Garcia
{"title":"Automatic Measures for Predicting Performance in Off-Line Signature","authors":"F. Alonso-Fernandez, M. Fairhurst, Julian Fierrez, J. Ortega-Garcia","doi":"10.1109/ICIP.2007.4378968","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4378968","url":null,"abstract":"Performance in terms of accuracy is one of the most important goal of a biometric system. Hence, having a measure which is able to predict the performance with respect to a particular sample of interest is specially useful, and can be exploited in a number of ways. In this paper, we present two automatic measures for predicting the performance in off-line signature verification. Results obtained on a sub-corpus of the MCYT signature database confirms a relationship between the proposed measures and system error rates measured in terms of equal error rate (EER), false acceptance rate (FAR) and false rejection rate (FRR).","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115415758","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: 57
Extension of Mutual Subspace Method for Low Dimensional Feature Projection 低维特征投影的互子空间扩展方法
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4379189
D. Veljkovic, K. Robbins, D. Rubino, N. Hatsopoulos
{"title":"Extension of Mutual Subspace Method for Low Dimensional Feature Projection","authors":"D. Veljkovic, K. Robbins, D. Rubino, N. Hatsopoulos","doi":"10.1109/ICIP.2007.4379189","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4379189","url":null,"abstract":"Face recognition algorithms based on mutual subspace methods (MSM) map segmented faces to single points on a feature manifold and then apply manifold learning techniques to classify the results. This paper proposes a generic extension to MSM for analysis of features in high-throughput recordings. We apply this method to analyze short duration overlapping waves in synthetic data and multielectrode brain recordings. We compare different feature space topologies and projection techniques, including MDS, ISOMAP and Laplacian eigenmaps. Overall we find that ISOMAP shows the least sensitivity to noise and provides the best association between distance in feature space and Euclidean distance in projection space. For non-noisy data, Laplacian eigenmaps show the least sensitivity to feature space topology.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115755382","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
A Greedy Performance Driven Algorithm for Decision Fusion Learning 一种贪婪性能驱动的决策融合学习算法
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4379512
D. Joshi, M. Naphade, A. Natsev
{"title":"A Greedy Performance Driven Algorithm for Decision Fusion Learning","authors":"D. Joshi, M. Naphade, A. Natsev","doi":"10.1109/ICIP.2007.4379512","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4379512","url":null,"abstract":"We propose a greedy performance driven algorithm for learning how to fuse across multiple classification and search systems. We assume a scenario when many such systems need to be fused to generate the final ranking. The algorithm is inspired from Ensemble Learning but takes that idea further for improving generalization capability. Fusion learning is applied to leverage text, visual and model based modalities for 2005 TRECVID query retrieval task. Experiments using the well established retrieval effectiveness measure of mean average precision reveal that our proposed algorithm improves over naive baseline (fusion with equal weights) as well as over Caruana's original algorithm (NACHOS) by 36% and 46% respectively.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125228162","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
Structure Preserving Image Interpolation via Adaptive 2D Autoregressive Modeling 基于自适应二维自回归建模的保结构图像插值
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4379987
Xiangjun Zhang, Xiaolin Wu
{"title":"Structure Preserving Image Interpolation via Adaptive 2D Autoregressive Modeling","authors":"Xiangjun Zhang, Xiaolin Wu","doi":"10.1109/ICIP.2007.4379987","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4379987","url":null,"abstract":"The performance of image interpolation depends on an image model that can adapt to nonstationary statistics of natural images when estimating the missing pixels. However, the construction of such an adaptive model needs the knowledge of every pixels that are absent. We resolve this dilemma by a new piecewise 2D autoregressive technique that builds the model and estimates the missing pixels jointly. This task is formulated as a non-linear optimization problem. Although computationally demanding, the new non-linear approach produces superior results than current methods in both PSNR and subjective visual quality. Moreover, in quest for a practical solution, we break the non-linear optimization problem into two subproblems of linear least-squares estimation. This linear approach proves very effective in our experiments.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116639314","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: 5
High Resolution Image Reconstruction in Shape from Focus 高分辨率图像重建的形状从焦点
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4379094
R. R. Sahay, A. Rajagopalan
{"title":"High Resolution Image Reconstruction in Shape from Focus","authors":"R. R. Sahay, A. Rajagopalan","doi":"10.1109/ICIP.2007.4379094","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4379094","url":null,"abstract":"In the Shape from Focus (SFF) method, a sequence of images of a 3D object is captured for computing its depth profile. However, it is useful in several applications to also derive a high resolution focused image of the 3D object. Given the space-variantly blurred frames and the depth map, we propose a method to optimally estimate a high resolution image of the object within the SFF framework.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117154293","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
New Features to Identify Computer Generated Images 识别计算机生成图像的新功能
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4380047
A. Dirik, Sevinc Bayram, H. Sencar, N. Memon
{"title":"New Features to Identify Computer Generated Images","authors":"A. Dirik, Sevinc Bayram, H. Sencar, N. Memon","doi":"10.1109/ICIP.2007.4380047","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4380047","url":null,"abstract":"Discrimination of computer generated images from real images is becoming more and more important. In this paper, we propose the use of new features to distinguish computer generated images from real images. The proposed features are based on the differences in the acquisition process of images. More specifically, traces of demosaicking and chromatic aberration are used to differentiate computer generated images from digital camera images. It is observed that the former features perform very well on high quality images, whereas the latter features perform consistently across a wide range of compression values. The experimental results show that proposed features are capable of improving the accuracy of the state-of-the-art techniques.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127167893","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: 96
Optimal Joint Source-Channel Coding using Unequal Error Protection for the Scalable Extension of H.264/MPEG-4 AVC 基于不等错误保护的H.264/MPEG-4 AVC可扩展的最优联合源信道编码
2007 IEEE International Conference on Image Processing Pub Date : 2007-11-12 DOI: 10.1109/ICIP.2007.4379635
M. Stoufs, A. Munteanu, P. Schelkens, J. Cornelis
{"title":"Optimal Joint Source-Channel Coding using Unequal Error Protection for the Scalable Extension of H.264/MPEG-4 AVC","authors":"M. Stoufs, A. Munteanu, P. Schelkens, J. Cornelis","doi":"10.1109/ICIP.2007.4379635","DOIUrl":"https://doi.org/10.1109/ICIP.2007.4379635","url":null,"abstract":"This paper proposes an optimized joint source-channel coding methodology with unequal error protection for the transmission of video encoded with the recently developed scalable extension of H.264/MPEG-4 AVC. The proposed methodology uses a simplified Viterbi-based search method which significantly outperforms the classical exhaustive search method in terms of computational complexity, leading to a practically applicable solution at the expense of a minimal loss of optimality. Experimental results show the effectiveness of our protection methodology and illustrate its capability to provide graceful degradation in the presence of channel mismatches.","PeriodicalId":131177,"journal":{"name":"2007 IEEE International Conference on Image Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127470038","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
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