Pub Date : 2010-07-07DOI: 10.1109/IPTA.2010.5586808
Changryoul Choi, Jechang Jeong
An improved two-bit transform-based motion estimation algorithm is proposed in this paper. By extending the typical two-bit transform (2BT) matching criterion, the proposed algorithm enhances the motion estimation accuracy with almost the same computational complexity, while preserving the binary matching characteristic. Experimental results show that the proposed algorithm achieves peak-to-peak signal-to-noise ratio (PSNR) gains of 0.29dB on average compared with the conventional 2BT-based motion estimation.
{"title":"Improved two-bit transform-based motion estimation via extension of matching criterion","authors":"Changryoul Choi, Jechang Jeong","doi":"10.1109/IPTA.2010.5586808","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586808","url":null,"abstract":"An improved two-bit transform-based motion estimation algorithm is proposed in this paper. By extending the typical two-bit transform (2BT) matching criterion, the proposed algorithm enhances the motion estimation accuracy with almost the same computational complexity, while preserving the binary matching characteristic. Experimental results show that the proposed algorithm achieves peak-to-peak signal-to-noise ratio (PSNR) gains of 0.29dB on average compared with the conventional 2BT-based motion estimation.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132444872","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586774
Qing Liu, Sun'an Wang, Xiaohui Zhang, Yun Hou
Based on the feature of CCD image forming, the internal principle of image forming is analyzed, and the loss of charge transfer is calculated by the Shockley - Read - Hall equation, in which the distribution function between the charge transfer is reconstructed. Rational polynomial interpolation algorithm is used to determine the unknown pixel points for the adjacent pixels that do not overcome the loss of charge transfer to enhance the image. It is an self-adaptive interpolation algorithm, in which the interpolation function can be adjusted automatically with electrical potential difference of the adjoining pixels and its energy zone, by means of which, the image can be magnified self-adaptively. Remote sensing image is tested, and the example results show that not only the image quality is improved, but also the clear margin and contour information is kept with this algorithm. And thus the processed images are more conducive to the naked eye.
{"title":"Improvement of the space resolution of the optical remote sensing image by the principle of CCD imaging","authors":"Qing Liu, Sun'an Wang, Xiaohui Zhang, Yun Hou","doi":"10.1109/IPTA.2010.5586774","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586774","url":null,"abstract":"Based on the feature of CCD image forming, the internal principle of image forming is analyzed, and the loss of charge transfer is calculated by the Shockley - Read - Hall equation, in which the distribution function between the charge transfer is reconstructed. Rational polynomial interpolation algorithm is used to determine the unknown pixel points for the adjacent pixels that do not overcome the loss of charge transfer to enhance the image. It is an self-adaptive interpolation algorithm, in which the interpolation function can be adjusted automatically with electrical potential difference of the adjoining pixels and its energy zone, by means of which, the image can be magnified self-adaptively. Remote sensing image is tested, and the example results show that not only the image quality is improved, but also the clear margin and contour information is kept with this algorithm. And thus the processed images are more conducive to the naked eye.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128504125","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586759
Yicong Zhou, K. Panetta, S. Agaian
This paper introduces a new mammogram enhancement algorithm using the human visual system (HVS) based image decomposition. A new enhancement measure based on the second derivative is also introduced to measure and assess the enhancement performance. Experimental results show that the presented algorithm can improve the visual quality of fine details in mammograms. The HVS-based image decomposition can segment the regions/objects from their surroundings. It offers the users flexibility to enhance either sub-images containing only significant illumination information or all the sub-images of the original mammograms. The algorithm can be used in the computer-aided diagnosis systems for breast cancer detection.
{"title":"Human visual system based mammogram enhancement and analysis","authors":"Yicong Zhou, K. Panetta, S. Agaian","doi":"10.1109/IPTA.2010.5586759","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586759","url":null,"abstract":"This paper introduces a new mammogram enhancement algorithm using the human visual system (HVS) based image decomposition. A new enhancement measure based on the second derivative is also introduced to measure and assess the enhancement performance. Experimental results show that the presented algorithm can improve the visual quality of fine details in mammograms. The HVS-based image decomposition can segment the regions/objects from their surroundings. It offers the users flexibility to enhance either sub-images containing only significant illumination information or all the sub-images of the original mammograms. The algorithm can be used in the computer-aided diagnosis systems for breast cancer detection.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129889032","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586809
D. T. Cong, C. Achard, L. Khoudour
The research presented in this paper consists in developing an automatic system for people re-identification across multiple cameras with non-overlapping fields of view. We first propose a robust algorithm for silhouette extraction which is based on an adaptive spatio-colorimetric background and foreground model coupled with a dynamic decision framework. Such a method is able to deal with the difficult conditions of outdoor environments where lighting is not stable and distracting motions are very numerous. A robust classification procedure, which exploits the discriminative nature of sparse representation, is then presented to perform people re-identification task. The global system is tested on two real data sets recorded in very difficult environments. The experimental results show that the proposed system leads to very satisfactory results compared to other approaches of the literature.
{"title":"People re-identification by classification of silhouettes based on sparse representation","authors":"D. T. Cong, C. Achard, L. Khoudour","doi":"10.1109/IPTA.2010.5586809","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586809","url":null,"abstract":"The research presented in this paper consists in developing an automatic system for people re-identification across multiple cameras with non-overlapping fields of view. We first propose a robust algorithm for silhouette extraction which is based on an adaptive spatio-colorimetric background and foreground model coupled with a dynamic decision framework. Such a method is able to deal with the difficult conditions of outdoor environments where lighting is not stable and distracting motions are very numerous. A robust classification procedure, which exploits the discriminative nature of sparse representation, is then presented to perform people re-identification task. The global system is tested on two real data sets recorded in very difficult environments. The experimental results show that the proposed system leads to very satisfactory results compared to other approaches of the literature.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131829365","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586772
N. Milisavljevic, D. Closson, I. Bloch
This paper describes detection and interpretation of temporal changes in an area of interest using coherent change detection in repeat-pass Synthetic Aperture Radar imagery, with the main goal of detecting subtle scene changes such as potential human activities. Possibilities of introducing knowledge sources in order to improve the final result are also presented.
{"title":"Detecting potential human activities using coherent change detection","authors":"N. Milisavljevic, D. Closson, I. Bloch","doi":"10.1109/IPTA.2010.5586772","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586772","url":null,"abstract":"This paper describes detection and interpretation of temporal changes in an area of interest using coherent change detection in repeat-pass Synthetic Aperture Radar imagery, with the main goal of detecting subtle scene changes such as potential human activities. Possibilities of introducing knowledge sources in order to improve the final result are also presented.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"101 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132236425","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586788
R. Pouteau, B. Stoll, S. Chabrier
One of the major stakeholders of image fusion is being able to process the most complex images at the finest possible integration level and with the most reliable accuracy. The use of support vector machine (SVM) fusion for the classification of multisensors images representing a complex tropical ecosystem is investigated. First, SVM are trained individually on a set of complementary sources: multispectral, synthetic aperture radar (SAR) images and a digital elevation model (DEM). Then a SVM-based decision fusion is performed on the three sources. SVM fusion outperforms all monosource classifications outputting results with the same accuracy as the majority of other comparable studies on cultural landscapes. SVM-based hybrid consensus classification does not only balance successful and misclassified results, it also uses misclassification patterns as information. Such a successful approach is partially due to the integration of DEM-extracted indices which are relevant to land cover mapping in non-cultural and topographically complex landscapes.
{"title":"Support vector machine fusion of multisensor imagery in tropical ecosystems","authors":"R. Pouteau, B. Stoll, S. Chabrier","doi":"10.1109/IPTA.2010.5586788","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586788","url":null,"abstract":"One of the major stakeholders of image fusion is being able to process the most complex images at the finest possible integration level and with the most reliable accuracy. The use of support vector machine (SVM) fusion for the classification of multisensors images representing a complex tropical ecosystem is investigated. First, SVM are trained individually on a set of complementary sources: multispectral, synthetic aperture radar (SAR) images and a digital elevation model (DEM). Then a SVM-based decision fusion is performed on the three sources. SVM fusion outperforms all monosource classifications outputting results with the same accuracy as the majority of other comparable studies on cultural landscapes. SVM-based hybrid consensus classification does not only balance successful and misclassified results, it also uses misclassification patterns as information. Such a successful approach is partially due to the integration of DEM-extracted indices which are relevant to land cover mapping in non-cultural and topographically complex landscapes.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124490517","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586762
Mauritz Panggabean, Stig Salater, L. A. Rønningen
This paper investigates the use of eye tracking to define the important objects in a scene, i.e. those focused by viewers. These objects are rich in information, such as human face. They should be coded with higher quality than unfocused ones as in foveated video coding, for which eye tracking can serve as a preliminary step. We show that human gaze points often cover only a very small area of the screen, even less than 10%, providing great opportunities to save much more bit rate. Gaze points from a number of subjects watching a scene can be represented compactly in the proposed box diagram, another contribution from this work, that can give simple description of the scene just in a one diagram.
{"title":"Eye tracking for foveation video coding and simple scene description","authors":"Mauritz Panggabean, Stig Salater, L. A. Rønningen","doi":"10.1109/IPTA.2010.5586762","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586762","url":null,"abstract":"This paper investigates the use of eye tracking to define the important objects in a scene, i.e. those focused by viewers. These objects are rich in information, such as human face. They should be coded with higher quality than unfocused ones as in foveated video coding, for which eye tracking can serve as a preliminary step. We show that human gaze points often cover only a very small area of the screen, even less than 10%, providing great opportunities to save much more bit rate. Gaze points from a number of subjects watching a scene can be represented compactly in the proposed box diagram, another contribution from this work, that can give simple description of the scene just in a one diagram.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129231289","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586739
A. Karami, M. Yazdi, A. Z. Asli
In this paper, an efficient method for Hyperspectral image compression based on the Tucker Decomposition (TD) and the Three Dimensional Discrete Cosine Transform (3D-DCT) is proposed. The core idea behind our proposed technique is to apply TD to the 3D-DCT coefficients of Hyperspectral image in order to not only exploit redundancies between bands but also to use spatial correlations of every image band and therefore, as simulation results applied to real Hyperspectral images demonstrate, it leads to a remarkable compression ratio with improved quality.
{"title":"Hyperspectral image compression based on Tucker Decomposition and Discrete Cosine Transform","authors":"A. Karami, M. Yazdi, A. Z. Asli","doi":"10.1109/IPTA.2010.5586739","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586739","url":null,"abstract":"In this paper, an efficient method for Hyperspectral image compression based on the Tucker Decomposition (TD) and the Three Dimensional Discrete Cosine Transform (3D-DCT) is proposed. The core idea behind our proposed technique is to apply TD to the 3D-DCT coefficients of Hyperspectral image in order to not only exploit redundancies between bands but also to use spatial correlations of every image band and therefore, as simulation results applied to real Hyperspectral images demonstrate, it leads to a remarkable compression ratio with improved quality.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129293054","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586741
Sang-Jun Park, Gwanggil Jeon, Jechang Jeong
The purpose of this article is to discuss deinterlacing results in a computationally constrained and varied environment. The proposed covariance-based adaptive deinterlacing method using edge map (CADEM) consists of two methods: the modified edge-based line averaging (MELA) method for plain regions and the covariance-based adaptive deinterlacing (CAD) method along the edges. The proposed CADEM uses the edge map of the interlaced input image for assigning the appropriate method between MELA and the modified CAD (MCAD) methods. We first introduce the MCAD method. The principle idea of the MCAD is based on the correspondence between the high-resolution covariance and the low-resolution covariance. The MCAD estimates the local covariance coefficients from an interlaced image using Wiener filtering theory and then uses these optimal minimum mean squared error interpolation coefficients to obtain a deinterlaced image. However, the MCAD method, though more robust than most known methods, was not found to be very fast compared with the others. To alleviate this issue, we propose an adaptive selection approach rather than using only one MCAD algorithm. The proposed hybrid approach of switching between the MELA and MCAD is proposed to reduce the overall computational load. A reliable condition to be used for switching the schemes is established by the edge map composed of binary image. The results of computer simulations showed that the proposed methods outperformed a number of methods presented in the literature.
{"title":"Covariance-based adaptive deinterlacing method using edge map","authors":"Sang-Jun Park, Gwanggil Jeon, Jechang Jeong","doi":"10.1109/IPTA.2010.5586741","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586741","url":null,"abstract":"The purpose of this article is to discuss deinterlacing results in a computationally constrained and varied environment. The proposed covariance-based adaptive deinterlacing method using edge map (CADEM) consists of two methods: the modified edge-based line averaging (MELA) method for plain regions and the covariance-based adaptive deinterlacing (CAD) method along the edges. The proposed CADEM uses the edge map of the interlaced input image for assigning the appropriate method between MELA and the modified CAD (MCAD) methods. We first introduce the MCAD method. The principle idea of the MCAD is based on the correspondence between the high-resolution covariance and the low-resolution covariance. The MCAD estimates the local covariance coefficients from an interlaced image using Wiener filtering theory and then uses these optimal minimum mean squared error interpolation coefficients to obtain a deinterlaced image. However, the MCAD method, though more robust than most known methods, was not found to be very fast compared with the others. To alleviate this issue, we propose an adaptive selection approach rather than using only one MCAD algorithm. The proposed hybrid approach of switching between the MELA and MCAD is proposed to reduce the overall computational load. A reliable condition to be used for switching the schemes is established by the edge map composed of binary image. The results of computer simulations showed that the proposed methods outperformed a number of methods presented in the literature.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125135047","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586756
Tomáš Fabián, Jan Gaura, Petr Kotas
In this paper, we describe a new method for detecting iris in digital images. Our method is simple yet effective. It is based on statistical point of view when searching for limbic boundary and rather analytical approach when detecting pupillary boundary. It can be described in three simple steps; firstly, the bright point inside the pupil is detected; secondly, outer limbic boundary is found via statistical measurements of outer boundary points; and thirdly, inner boundary points are found by means of defined cost function maximization. Performance of the presented method is evaluated on series of iris close-up images and compared with the traditional Hough method as well.
{"title":"An algorithm for iris extraction","authors":"Tomáš Fabián, Jan Gaura, Petr Kotas","doi":"10.1109/IPTA.2010.5586756","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586756","url":null,"abstract":"In this paper, we describe a new method for detecting iris in digital images. Our method is simple yet effective. It is based on statistical point of view when searching for limbic boundary and rather analytical approach when detecting pupillary boundary. It can be described in three simple steps; firstly, the bright point inside the pupil is detected; secondly, outer limbic boundary is found via statistical measurements of outer boundary points; and thirdly, inner boundary points are found by means of defined cost function maximization. Performance of the presented method is evaluated on series of iris close-up images and compared with the traditional Hough method as well.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122889918","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}
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