{"title":"Video inpainting of occluding and occluded objects","authors":"K. A. Patwardhan, G. Sapiro, M. Bertalmío","doi":"10.1109/ICIP.2005.1529993","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1529993","url":null,"abstract":"We present a basic technique to fill-in missing parts of a video sequence taken from a static camera. Two important cases are considered. The first case is concerned with the removal of non-stationary objects that occlude stationary background. We use a priority based spatio-temporal synthesis scheme for inpainting the stationary background. The second and more difficult case involves filling-in moving objects when they are partially occluded. For this, we propose a priority scheme to first inpaint the occluded moving objects and then fill-in the remaining area with stationary background using the method proposed for the first case. We use as input an optical-flow based mask, which tells if an undamaged pixel is moving or is stationary. The moving object is inpainted by copying patches from undamaged frames, and this copying is independent of the background of the moving object in either frame. This work has applications in a variety of different areas, including video special effects and restoration and enhancement of damaged videos. The examples shown in the paper illustrate these ideas.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127670643","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}
{"title":"Color texture retrieval through contourlet-based hidden Markov model","authors":"Zhihua He, M. Bystrom","doi":"10.1109/ICIP.2005.1529800","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1529800","url":null,"abstract":"Two statistical models for color texture retrieval based on a hidden Markov model (HMM) in the contourlet domain are described in this paper. Through a contourlet transformation, each color component of an image is decomposed into a set of directional subbands with texture details captured in different orientations. By exploiting inter-scale dependencies and in-band spatial dependencies, the distribution of the coefficients in each subband triplet (subbands of three color components at the same scale with the same orientation) can be estimated using a vector hidden Markov model. The Kullback-Leibler distance (KLD) is used to measure the difference between the distributions of query texture images and those of images in the database. The experimental results show the proposed retrieval systems yield high retrieval rates and better visual quality as compared with previous methods employing hidden Markov models for luminance component alone.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127726528","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}
Dong Wang, C. N. Canagarajah, D. Agrafiotis, D. Bull
{"title":"Error concealment for slice group based multiple description video coding","authors":"Dong Wang, C. N. Canagarajah, D. Agrafiotis, D. Bull","doi":"10.1109/ICIP.2005.1529864","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1529864","url":null,"abstract":"This paper develops error concealment methods for multiple description video coding (MDC) in order to adapt to error prone packet networks. The three-loop slice group MDC approach of D. Wang et al. (2005) is used. MDC is very suitable for multiple channel environments, and especially able to maintain acceptable quality when some of these channels fail completely, i.e. in an on-off MDC environment, without experiencing any drifting problem. Our MDC scheme coupled with the proposed concealment approaches proved to be suitable not only for the on-off MDC environment case (data from one channel fully lost), but also for the case where only some packets are lost from one or both channels. Copying video and using motion vectors from correct descriptions are combined together for concealment prior to applying traditional methods. Results are compared to the traditional error concealment method proposed in the H.264 reference software, showing significant improvements for both the balanced and unbalanced channel cases.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126217551","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}
{"title":"New image transforms using hybrid wavelets and directional filter banks: analysis and design","authors":"R. Eslami, H. Radha","doi":"10.1109/ICIP.2005.1529855","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1529855","url":null,"abstract":"We propose a new family of perfect reconstruction, non-redundant, and multiresolution geometrical image transforms using the wavelet transform in conjunction with modified versions of directional filter banks (DFB). In the proposed versions of DFB, we use either horizontal or vertical directional decomposition. Taking advantage of the wavelet transform that has efficient nonlinear approximation property, we add the important feature of directionality by applying the modified and regular DFB to the subbands of a few finest wavelet levels. This way we can eliminate a major portion of the artifacts usually introduced when DFB are used. The proposed hybrid wavelets and DFB (HWD) transform family provides visual and PSNR improvements over the wavelet and contourlet transforms.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128063887","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}
{"title":"Content adaptive watermarking using a 2-stage predictor","authors":"S. Yip, O. Au, C. Ho, H. Wong","doi":"10.1109/ICIP.2005.1529910","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1529910","url":null,"abstract":"Digital watermarking is one of the solutions to protect intellectual properties and copyright by hiding information, such as a random sequence or a logo, into digital media. In this paper, a new watermarking scheme is proposed. The embedding process takes place in the spatial domain. A bi-level logo is embedded into digital media by comparing the absolute difference between the original pixel value and the predicted pixel value, which is computed and predicted by using the concept of activity measurement, followed by spatial varying filter (SVF). The logo will be extracted from a possibly corrupted image, without the help of original uncorrupted image. The new proposed algorithm can withstand the geometric attacks as well as common signal processing, and has a high payload capacity.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128071582","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}
{"title":"A Fourier interpretation of super-resolution techniques","authors":"F. Champagnat, G. L. Besnerais","doi":"10.1109/ICIP.2005.1529888","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1529888","url":null,"abstract":"We are concerned with analysis of linear reconstruction-based super-resolution (SR) techniques. We propose a novel Fourier interpretation of an \"archetype\" linear SR algorithm and derive practical results on the expected performances of such techniques.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125722043","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}
{"title":"Shape space sampling distributions and their impact on visual tracking","authors":"A. Kale, C. Jaynes","doi":"10.1109/ICIP.2005.1529708","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1529708","url":null,"abstract":"Object motions can be represented as a sequence of shape deformations and translations which can be interpretated as a sequence of points in N-dimensional shape space. These spaces range from simple 2D translations to more inclusive spaces such as the affine. In this case, tracking is the problem of inferring the most likely point in the space for the next frame given a current set of hypotheses. A robust method for achieving this is the particle filter. In this case, likely points within shape space are selected in a two step process. First, image measurements assign likelihoods to proposed points. Likely points are then propagated forward using a dynamical model to derive a set of new points that are perturbed according to some sampling distribution. These distributions play an important role in tracking performance because dynamical models are seldom known and a Gauss Markov model is often assumed for the model dynamics. This paper address the problems inherent in utilizing uninformed sampling distributions for visual tracking. We introduce a principled adaptive sampling approach that takes into account constraints on each component of the shape vector. Further a more appropriate sampling distribution that takes place in a linear subspace representing the predominant motion in the shape space. Results demonstrate improved tracking performance in challenging conditions where targets exhibit changing motion models.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128175854","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}
{"title":"Optimization of cluster coverage for road centre-line extraction in high resolution satellite images","authors":"Seifeddine Ferchichi, Shengrui Wang","doi":"10.1109/ICIP.2005.1530026","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1530026","url":null,"abstract":"This paper presents a new approach for road centre-line extraction from high-resolution images, based on cluster coverage. The idea is first to segment the image; in order to obtain road candidates. Then we apply the k-means algorithm to cluster the pixels of the segmented image. The resulting clusters cover the road and the noise generated by the segmentation process. We introduce the concept of cluster coverage to remove noise and to approximate the optimal number of clusters that fit the shape of the road.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132113592","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}
{"title":"3D wavelet video coding with replicated matching pursuits","authors":"Yuan Yuan, D. Monro","doi":"10.1109/ICIP.2005.1529689","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1529689","url":null,"abstract":"Improved coding of 3D spatio-temporal wavelet video is achieved using matching pursuits (MP) with a separable 2D basis dictionary and temporal replication of atoms. Using two temporal scales and the biorthogonal 5/3 wavelet filter incorporating motion compensation, four sets of four transform planes are combined into a group of temporal planes (GOTP). The planes are wavelet transformed to 4 scales spatially before the 2D MP algorithm is applied over the entire GOTP to select the optimum inner product with a 2D dictionary of 64 bases formed separably from 8 ID basis functions. The selected atom is conditionally replicated in the three corresponding temporal frequency planes within the GOTP. Compared to applying 2D MP to the planes without replication, a gain of up to 2 dB has been achieved. Comparisons with a standard H.263 codec and the classic MP enhanced H.263 MP codec, show significant gains at low bit rates.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132549505","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}
{"title":"Multiple blocks update algorithm for matching pursuit video coding","authors":"Jian-Liang Lin, W. Hwang, S. Pei","doi":"10.1109/ICIP.2005.1530041","DOIUrl":"https://doi.org/10.1109/ICIP.2005.1530041","url":null,"abstract":"Matching pursuit (MP) video coding has been demonstrated to attain a better coding performance than DCT-based video coding in terms of PSNR and perceptual quality at very low bit rates. However, because of its massive computational complexity, the MP algorithm is usually only approximated. By approximating a residual in a subspace, we propose a multiple blocks search and update algorithm in MP video coding to achieve a faster and better MP approximation. In this paper, we evaluate the performance and compare it to the traditional one-block search algorithms. The experimental results show that our proposed algorithm can significantly improve the coding performance and encoding time.","PeriodicalId":295452,"journal":{"name":"IEEE International Conference on Image Processing 2005","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130274894","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}