Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing最新文献
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.648074
A. Vetro, Huifang Sun, J. Bao, T. Poon
The paper investigates the possible means of down converting an incoming HDTV signal into one which is suitable for display onto an NTSC monitor. We present a novel frequency synthesis algorithm which constructs a set of 8/spl times/8 DCT coefficients from four original 8/spl times/8 DCT blocks. Also, a down-conversion decoder employing a unique adaptive motion compensation algorithm is presented. Using this fixed motion compensation algorithm, the proposed down-conversion technique is compared to the conventional method. Both yield acceptable image sequences with different trade-offs in complexity and quality.
{"title":"Frequency domain down-conversion of HDTV using adaptive motion compensation","authors":"A. Vetro, Huifang Sun, J. Bao, T. Poon","doi":"10.1109/ICIP.1997.648074","DOIUrl":"https://doi.org/10.1109/ICIP.1997.648074","url":null,"abstract":"The paper investigates the possible means of down converting an incoming HDTV signal into one which is suitable for display onto an NTSC monitor. We present a novel frequency synthesis algorithm which constructs a set of 8/spl times/8 DCT coefficients from four original 8/spl times/8 DCT blocks. Also, a down-conversion decoder employing a unique adaptive motion compensation algorithm is presented. Using this fixed motion compensation algorithm, the proposed down-conversion technique is compared to the conventional method. Both yield acceptable image sequences with different trade-offs in complexity and quality.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"1 1","pages":"763-766 vol.1"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72695131","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}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.647763
S. Suthaharan, Zhongwei Zhang
A new technique based a genetic algorithm is proposed in this paper to find the optimal value of the ratio /spl Gamma/, which is a priori knowledge of the signal-to-noise ratio, in the Wiener filter for image restoration. The proposed method can be used in a control experiment in conjunction with any image-quality-assessment measure in order to obtain the optimal /spl Gamma/ for the measure. In the control experiment, the minimum mean square error (MSE) and image activity weighted error (IAWE) are used.
{"title":"SNR optimisation using genetic algorithm","authors":"S. Suthaharan, Zhongwei Zhang","doi":"10.1109/ICIP.1997.647763","DOIUrl":"https://doi.org/10.1109/ICIP.1997.647763","url":null,"abstract":"A new technique based a genetic algorithm is proposed in this paper to find the optimal value of the ratio /spl Gamma/, which is a priori knowledge of the signal-to-noise ratio, in the Wiener filter for image restoration. The proposed method can be used in a control experiment in conjunction with any image-quality-assessment measure in order to obtain the optimal /spl Gamma/ for the measure. In the control experiment, the minimum mean square error (MSE) and image activity weighted error (IAWE) are used.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"228 1","pages":"295-297 vol.1"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74985828","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}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.631986
M. Niimi, H. Noda, E. Kawaguchi
This paper describes a new technique to embed secret data into a dummy image by using image segmentation based on a local complexity measure. The key idea to this approach is that a binary image can be categorized as "informative" and "noise-like" regions which are segmented by a "complexity measure". If the embedding data is noise-like, we can hide it in the noise-like region of the dummy image. If a part of embedding data is simple, then we apply "image conjugate" operation to it. This operation transform a simple pattern into a complex pattern. In our experiment, we could embed two color images in a 512/spl times/512 (8 bits/pixel) size gray image (which was dummy) without losing any information. The total amount of the two embedded images was 115 KB, which was about 45% of the dummy image.
{"title":"An image embedding in image by a complexity based region segmentation method","authors":"M. Niimi, H. Noda, E. Kawaguchi","doi":"10.1109/ICIP.1997.631986","DOIUrl":"https://doi.org/10.1109/ICIP.1997.631986","url":null,"abstract":"This paper describes a new technique to embed secret data into a dummy image by using image segmentation based on a local complexity measure. The key idea to this approach is that a binary image can be categorized as \"informative\" and \"noise-like\" regions which are segmented by a \"complexity measure\". If the embedding data is noise-like, we can hide it in the noise-like region of the dummy image. If a part of embedding data is simple, then we apply \"image conjugate\" operation to it. This operation transform a simple pattern into a complex pattern. In our experiment, we could embed two color images in a 512/spl times/512 (8 bits/pixel) size gray image (which was dummy) without losing any information. The total amount of the two embedded images was 115 KB, which was about 45% of the dummy image.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"16 1","pages":"74-77 vol.3"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75124457","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}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.648030
N. Harvey, S. Marshall
In any field which makes use of images, corruption is a common problem. For broadcasters, it is desirable to have processes capable of removing unwanted corruption in archive video material prior to broadcast. A method of video restoration is described which specifically addresses the problem of video "scratching".
{"title":"Application of non-linear image processing: digital video restoration","authors":"N. Harvey, S. Marshall","doi":"10.1109/ICIP.1997.648030","DOIUrl":"https://doi.org/10.1109/ICIP.1997.648030","url":null,"abstract":"In any field which makes use of images, corruption is a common problem. For broadcasters, it is desirable to have processes capable of removing unwanted corruption in archive video material prior to broadcast. A method of video restoration is described which specifically addresses the problem of video \"scratching\".","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"118 1","pages":"731-734 vol.1"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77403775","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}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.631979
Jiebo Luo, R. T. Gray, Hsien-Che Lee
In many digital image processing applications, image segmentation is required to provide initial partitioning of local image regions based on certain statistical or contextual homogeneity measures. One goal of image segmentation would be to segment the image into regions that correspond to physically and semantically coherent objects in the scene. We propose an improved color segmentation algorithm by taking advantage of a simple "k-mode" algorithm and an adaptive Bayesian k-means algorithm. The "k-mode" algorithm uses a physics-based distance metric to generate regular partitioning of the color space. The adaptive k-means algorithm utilizes two additional mechanisms, i.e., spatial homogeneity constraints and spatial adaptivity, to achieve more robust and coherent segmentation. The proposed algorithm integrates a physically more meaningful color space and the corresponding color difference metric into the the adaptive Bayesian K-means framework in an effort towards physics-based segmentation of photographic color images.
{"title":"Towards physics-based segmentation of photographic color images","authors":"Jiebo Luo, R. T. Gray, Hsien-Che Lee","doi":"10.1109/ICIP.1997.631979","DOIUrl":"https://doi.org/10.1109/ICIP.1997.631979","url":null,"abstract":"In many digital image processing applications, image segmentation is required to provide initial partitioning of local image regions based on certain statistical or contextual homogeneity measures. One goal of image segmentation would be to segment the image into regions that correspond to physically and semantically coherent objects in the scene. We propose an improved color segmentation algorithm by taking advantage of a simple \"k-mode\" algorithm and an adaptive Bayesian k-means algorithm. The \"k-mode\" algorithm uses a physics-based distance metric to generate regular partitioning of the color space. The adaptive k-means algorithm utilizes two additional mechanisms, i.e., spatial homogeneity constraints and spatial adaptivity, to achieve more robust and coherent segmentation. The proposed algorithm integrates a physically more meaningful color space and the corresponding color difference metric into the the adaptive Bayesian K-means framework in an effort towards physics-based segmentation of photographic color images.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"71 1","pages":"58-61 vol.3"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77547773","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}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.638669
Jungwoo Lee
A new bit allocation technique between motion vectors and DCT coefficients for MPEG-2 encoding is presented. In MPEG-2 encoding, the differential between two neighboring motion vectors is losslessly encoded by a Huffman table. In order to adjust the bit allocation for the motion vectors, a motion vector smoothing approach is taken. The motion vectors are smoothed by a low pass filter when the bit allocation for the motion vector has to be reduced. An algorithm based on the Lagrange multiplier is used to achieve the optimal balance between motion vector smoothing and DCT coefficients quantization.
{"title":"Rate-distortion optimized motion smoothing for MPEG-2 encoding","authors":"Jungwoo Lee","doi":"10.1109/ICIP.1997.638669","DOIUrl":"https://doi.org/10.1109/ICIP.1997.638669","url":null,"abstract":"A new bit allocation technique between motion vectors and DCT coefficients for MPEG-2 encoding is presented. In MPEG-2 encoding, the differential between two neighboring motion vectors is losslessly encoded by a Huffman table. In order to adjust the bit allocation for the motion vectors, a motion vector smoothing approach is taken. The motion vectors are smoothed by a low pass filter when the bit allocation for the motion vector has to be reduced. An algorithm based on the Lagrange multiplier is used to achieve the optimal balance between motion vector smoothing and DCT coefficients quantization.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"229 1","pages":"45-48 vol.2"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77592263","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}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.638630
K. Sivakumar, J. Goutsias
We propose a class of Gibbs random fields which incorporate geometric information into stochastic image modeling by means of morphological constraints. This class is shown to be capable of modeling shapes with given morphological size density. Simulation examples illustrate some model properties.
{"title":"Morphologically constrained Gibbs random fields","authors":"K. Sivakumar, J. Goutsias","doi":"10.1109/ICIP.1997.638630","DOIUrl":"https://doi.org/10.1109/ICIP.1997.638630","url":null,"abstract":"We propose a class of Gibbs random fields which incorporate geometric information into stochastic image modeling by means of morphological constraints. This class is shown to be capable of modeling shapes with given morphological size density. Simulation examples illustrate some model properties.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"140 1","pages":"851-854 vol.2"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78171702","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}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.638798
P. Gamba, Massimilano Lilla, A. Mecocci
This paper proposes a new algorithm which applies perceptual grouping to track discontinuous chains of symbols in digitized maps. The procedure is based on an artificial intelligence kernel that supervises three different auxiliary processes: the search strategy generation module, responsible for the strategy to scan pixels; the symbol detection module that extracts the recognized symbols; the cost function evaluation module that assigns a global quality index to each symbol by considering the whole course of the line. Selected Gestalt rules are used to optimize the grouping procedures.
{"title":"Extraction of discontinuous chains of symbols by means of perceptual grouping","authors":"P. Gamba, Massimilano Lilla, A. Mecocci","doi":"10.1109/ICIP.1997.638798","DOIUrl":"https://doi.org/10.1109/ICIP.1997.638798","url":null,"abstract":"This paper proposes a new algorithm which applies perceptual grouping to track discontinuous chains of symbols in digitized maps. The procedure is based on an artificial intelligence kernel that supervises three different auxiliary processes: the search strategy generation module, responsible for the strategy to scan pixels; the symbol detection module that extracts the recognized symbols; the cost function evaluation module that assigns a global quality index to each symbol by considering the whole course of the line. Selected Gestalt rules are used to optimize the grouping procedures.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"118 1","pages":"422-425 vol.2"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80298248","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}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.632199
Bo Tao, M. Orchard, B. Dickinson
Motion uncertainty and image quantization noise are two important factors affecting the performance of block motion compensation in a standard hybrid video coder. This paper models both these effects, and analyzes their nonstationary property. It proposes a strategy that jointly applies space-varying overlapped block motion compensation and loop filtering, achieving better rate-distortion performance than either method alone.
{"title":"Joint application of overlapped block motion compensation and loop filtering for low bit-rate video coding","authors":"Bo Tao, M. Orchard, B. Dickinson","doi":"10.1109/ICIP.1997.632199","DOIUrl":"https://doi.org/10.1109/ICIP.1997.632199","url":null,"abstract":"Motion uncertainty and image quantization noise are two important factors affecting the performance of block motion compensation in a standard hybrid video coder. This paper models both these effects, and analyzes their nonstationary property. It proposes a strategy that jointly applies space-varying overlapped block motion compensation and loop filtering, achieving better rate-distortion performance than either method alone.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"37 3 1","pages":"626-629 vol.3"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80480284","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}
Pub Date : 1997-10-26DOI: 10.1109/ICIP.1997.647387
P. Csillag, L. Böröczky
In this paper a new iterative motion-based segmentation algorithm is presented for object-based video coding. At first, dense motion fields between image pairs are obtained by a multiresolution motion estimation algorithm. Based on these motion fields a set of global motion vectors are determined by an iterative vector quantisation procedure. Using the global motion vectors, the images are segmented into homogenous regions. Covered and uncovered areas of the background and objects are properly recognized by examining two consecutive motion fields. Experimental results for artificial as well for real-life video have shown that the proposed algorithm results in good quality segmentation label fields while it requires only moderate computations.
{"title":"Iterative motion-based segmentation for object-based video coding","authors":"P. Csillag, L. Böröczky","doi":"10.1109/ICIP.1997.647387","DOIUrl":"https://doi.org/10.1109/ICIP.1997.647387","url":null,"abstract":"In this paper a new iterative motion-based segmentation algorithm is presented for object-based video coding. At first, dense motion fields between image pairs are obtained by a multiresolution motion estimation algorithm. Based on these motion fields a set of global motion vectors are determined by an iterative vector quantisation procedure. Using the global motion vectors, the images are segmented into homogenous regions. Covered and uncovered areas of the background and objects are properly recognized by examining two consecutive motion fields. Experimental results for artificial as well for real-life video have shown that the proposed algorithm results in good quality segmentation label fields while it requires only moderate computations.","PeriodicalId":92344,"journal":{"name":"Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing","volume":"2 1","pages":"73-76 vol.1"},"PeriodicalIF":0.0,"publicationDate":"1997-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79027148","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}
Computer analysis of images and patterns : proceedings of the ... International Conference on Automatic Image Processing. International Conference on Automatic Image Processing
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