[ { "key": "3G4I3XHN", "version": 1, "library": { "type": "group", "id": 56888, "name": "image series segmentation", "links": { "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/56888/items/3G4I3XHN", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation/items/3G4I3XHN", "type": "text/html" } }, "meta": { "createdByUser": { "id": 777898, "username": "Mahir Nozinovic", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/mahir_nozinovic", "type": "text/html" } } }, "creatorSummary": "Aslantas and Kurban", "parsedDate": "2010-12", "numChildren": 0 }, "data": { "key": "3G4I3XHN", "version": 1, "itemType": "journalArticle", "title": "Fusion of multi-focus images using differential evolution algorithm", "creators": [ { "creatorType": "author", "firstName": "V.", "lastName": "Aslantas" }, { "creatorType": "author", "firstName": "R.", "lastName": "Kurban" } ], "abstractNote": "In an image captured by a CCD/CMOS sensor with an optical lens, only the objects within the depth of field are sharply focused. One way to get an everywhere-in-focus image is to fuse the images of the same scene which are taken with different focal settings. In this paper, a novel optimal method for multi-focus image fusion using differential evolution algorithm is presented. The source images are first decomposed into blocks. Then, the sharper blocks are selected by employing a sharpness criterion function. The selected blocks are finally combined to construct the fused image. The motivation of the proposed method lies in the fact that an optimized block size could be more effective than a fixed block size. Experimental results show that the proposed method outperforms other traditional methods and genetic algorithm based method in terms of both quantitative and visual evaluations.", "publicationTitle": "Expert Systems with Applications", "publisher": "", "place": "", "date": "December 2010", "volume": "37", "issue": "12", "section": "", "partNumber": "", "partTitle": "", "pages": "8861-8870", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1016/j.eswa.2010.06.011", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S0957417410005154", "accessDate": "2011-11-01T12:28:40Z", "PMID": "", "PMCID": "", "ISSN": "0957-4174", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Differential evolution algorithm", "type": 1 }, { "tag": "Extended depth of field", "type": 1 }, { "tag": "Genetic algorithm", "type": 1 }, { "tag": "Multi-focus image fusion", "type": 1 }, { "tag": "Sharpness metrics", "type": 1 } ], "collections": [ "Q4662AA8" ], "relations": {}, "dateAdded": "2011-11-01T13:07:31Z", "dateModified": "2011-11-01T13:07:31Z" } }, { "key": "6DQ9SU5S", "version": 1, "library": { "type": "group", "id": 56888, "name": "image series segmentation", "links": { "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/56888/items/6DQ9SU5S", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation/items/6DQ9SU5S", "type": "text/html" } }, "meta": { "createdByUser": { "id": 777898, "username": "Mahir Nozinovic", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/mahir_nozinovic", "type": "text/html" } } }, "creatorSummary": "Chai et al.", "numChildren": 0 }, "data": { "key": "6DQ9SU5S", "version": 1, "itemType": "journalArticle", "title": "Multifocus image fusion based on features contrast of multiscale products in nonsubsampled contourlet transform domain", "creators": [ { "creatorType": "author", "firstName": "Yi", "lastName": "Chai" }, { "creatorType": "author", "firstName": "Huafeng", "lastName": "Li" }, { "creatorType": "author", "firstName": "Xiaoyang", "lastName": "Zhang" } ], "abstractNote": "In this paper, an efficient multifocus image fusion approach is proposed based on local features contrast of multiscale products in nonsubsampled contourlet transform (NSCT) domain. In order to improve the robustness of the fusion algorithm to the noise and select the coefficients of the fused image properly, the multiscale products, which can distinguish edge structures from noise more effectively in NSCT domain, is developed and introduced into image fusion field. The selection principles of different subband coefficients obtained by the NSCT decomposition are discussed in detail. To improve the quality of the fused image, novel different local features contrast measurements, which are proved to be more suitable for human vision system and can extract more useful detail information from source images and inject them into the fused image, are developed and used to select coefficients from the clear parts of subimages to compose coefficients of fused images. Experimental results demonstrate the proposed method performs very well in fusion both noisy and noise-free multifocus images, and outperform conventional methods in terms of both visual quality and objective evaluation criteria.", "publicationTitle": "Optik - International Journal for Light and Electron Optics", "publisher": "", "place": "", "date": "", "volume": "", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1016/j.ijleo.2011.02.034", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S0030402611002579", "accessDate": "2011-11-01T12:31:54Z", "PMID": "", "PMCID": "", "ISSN": "0030-4026", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Image fusion", "type": 1 }, { "tag": "Local features contrast.", "type": 1 }, { "tag": "Multiscale products (MSP)", "type": 1 }, { "tag": "Nonsubsampled contourlet transform (NSCT)", "type": 1 } ], "collections": [ "Q4662AA8" ], "relations": {}, "dateAdded": "2011-11-01T13:07:22Z", "dateModified": "2011-11-01T13:07:22Z" } }, { "key": "DXTNV27A", "version": 1, "library": { "type": "group", "id": 56888, "name": "image series segmentation", "links": { "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/56888/items/DXTNV27A", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation/items/DXTNV27A", "type": "text/html" } }, "meta": { "createdByUser": { "id": 777898, "username": "Mahir Nozinovic", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/mahir_nozinovic", "type": "text/html" } } }, "creatorSummary": "Lewis et al.", "parsedDate": "2007-04", "numChildren": 0 }, "data": { "key": "DXTNV27A", "version": 1, "itemType": "journalArticle", "title": "Pixel- and region-based image fusion with complex wavelets", "creators": [ { "creatorType": "author", "firstName": "John J.", "lastName": "Lewis" }, { "creatorType": "author", "firstName": "Robert J.", "lastName": "O’Callaghan" }, { "creatorType": "author", "firstName": "Stavri G.", "lastName": "Nikolov" }, { "creatorType": "author", "firstName": "David R.", "lastName": "Bull" }, { "creatorType": "author", "firstName": "Nishan", "lastName": "Canagarajah" } ], "abstractNote": "A number of pixel-based image fusion algorithms (using averaging, contrast pyramids, the discrete wavelet transform and the dual-tree complex wavelet transform (DT-CWT) to perform fusion) are reviewed and compared with a novel region-based image fusion method which facilitates increased flexibility with the definition of a variety of fusion rules. A DT-CWT is used to segment the features of the input images, either jointly or separately, to produce a region map. Characteristics of each region are calculated and a region-based approach is used to fuse the images, region-by-region, in the wavelet domain. This method gives results comparable to the pixel-based fusion methods as shown using a number of metrics. Despite an increase in complexity, region-based methods have a number of advantages over pixel-based methods. These include: the ability to use more intelligent semantic fusion rules; and for regions with certain properties to be attenuated or accentuated.", "publicationTitle": "Information Fusion", "publisher": "", "place": "", "date": "April 2007", "volume": "8", "issue": "2", "section": "", "partNumber": "", "partTitle": "", "pages": "119-130", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1016/j.inffus.2005.09.006", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S1566253505000862", "accessDate": "2011-11-01T12:32:03Z", "PMID": "", "PMCID": "", "ISSN": "1566-2535", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Complex wavelets", "type": 1 }, { "tag": "Feature-based fusion", "type": 1 }, { "tag": "Image fusion", "type": 1 }, { "tag": "Region-based fusion", "type": 1 }, { "tag": "Segmentation", "type": 1 } ], "collections": [ "Q4662AA8" ], "relations": {}, "dateAdded": "2011-11-01T13:06:47Z", "dateModified": "2011-11-01T13:06:47Z" } }, { "key": "28F4UNVP", "version": 1, "library": { "type": "group", "id": 56888, "name": "image series segmentation", "links": { "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/56888/items/28F4UNVP", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation/items/28F4UNVP", "type": "text/html" } }, "meta": { "createdByUser": { "id": 777898, "username": "Mahir Nozinovic", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/mahir_nozinovic", "type": "text/html" } } }, "creatorSummary": "A. Ardeshir", "parsedDate": "2005-06-01", "numChildren": 0 }, "data": { "key": "28F4UNVP", "version": 1, "itemType": "journalArticle", "title": "Fusion of multi-exposure images", "creators": [ { "creatorType": "author", "firstName": "Goshtasby", "lastName": "A. Ardeshir" } ], "abstractNote": "A method for fusing multi-exposure images of a static scene taken by a stationary camera into an image with maximum information content is introduced. The method partitions the image domain into uniform blocks and for each block selects the image that contains the most information within that block. The selected images are then blended together using monotonically decreasing blending functions that are centered at the blocks and have a sum of 1 everywhere in the image domain. The optimal block size and width of the blending functions are determined using a gradient-ascent algorithm to maximize information content in the fused image.", "publicationTitle": "Image and Vision Computing", "publisher": "", "place": "", "date": "June 1, 2005", "volume": "23", "issue": "6", "section": "", "partNumber": "", "partTitle": "", "pages": "611-618", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1016/j.imavis.2005.02.004", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S0262885605000259", "accessDate": "2011-11-01T12:36:20Z", "PMID": "", "PMCID": "", "ISSN": "0262-8856", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Image blending", "type": 1 }, { "tag": "Image entropy", "type": 1 }, { "tag": "Image fusion", "type": 1 }, { "tag": "Image information", "type": 1 }, { "tag": "Multi-exposure", "type": 1 } ], "collections": [ "Q4662AA8" ], "relations": {}, "dateAdded": "2011-11-01T13:06:39Z", "dateModified": "2011-11-01T13:06:39Z" } }, { "key": "TG4MPJE8", "version": 1, "library": { "type": "group", "id": 56888, "name": "image series segmentation", "links": { "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/56888/items/TG4MPJE8", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation/items/TG4MPJE8", "type": "text/html" } }, "meta": { "createdByUser": { "id": 777898, "username": "Mahir Nozinovic", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/mahir_nozinovic", "type": "text/html" } } }, "creatorSummary": "Jo and Vavilin", "parsedDate": "2011-09", "numChildren": 0 }, "data": { "key": "TG4MPJE8", "version": 1, "itemType": "journalArticle", "title": "HDR Image Generation based on Intensity Clustering and Local Feature Analysis", "creators": [ { "creatorType": "author", "firstName": "Kang-Hyun", "lastName": "Jo" }, { "creatorType": "author", "firstName": "Andrey", "lastName": "Vavilin" } ], "abstractNote": "This paper describes a cluster-based method for combining differently exposed images in order to increase their dynamic range. Initially an image is decomposed into a set of arbitrary shaped regions. For each region we compute a utility function which is based on the amount of presented information and an entropy. This function is used to select the most appropriate exposure for each region. After the exposures are selected, a bilateral filtering is applied in order to make the interregional transitions smooth. As a result we obtain weighting coefficients for each exposure and pixel. An output image is combined from clusters of input images using weights. Each pixel of the output image is calculated as a weighted sum of exposures. The proposed method allows recovering details from overexposed and underexposed parts of image without producing additional noise. Our experiments show effectiveness of the algorithm for the high dynamic range scenes. It requires no information about shutter speed or camera parameters. This method shows robust results even if the exposure difference between input images is 2-stops or higher.", "publicationTitle": "Computers in Human Behavior", "publisher": "", "place": "", "date": "September 2011", "volume": "27", "issue": "5", "section": "", "partNumber": "", "partTitle": "", "pages": "1507-1511", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1016/j.chb.2010.10.015", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S0747563210003134", "accessDate": "2011-11-01T12:50:12Z", "PMID": "", "PMCID": "", "ISSN": "0747-5632", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Bilateral filtering", "type": 1 }, { "tag": "HDR", "type": 1 }, { "tag": "Image clustering", "type": 1 }, { "tag": "Local feature analysis", "type": 1 } ], "collections": [ "Q4662AA8" ], "relations": {}, "dateAdded": "2011-11-01T13:06:25Z", "dateModified": "2011-11-01T13:06:25Z" } }, { "key": "MAWWPVGZ", "version": 1, "library": { "type": "group", "id": 56888, "name": "image series segmentation", "links": { "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/56888/items/MAWWPVGZ", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation/items/MAWWPVGZ", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/56888/items/XPXZ5665", "type": "application/json" } }, "meta": { "createdByUser": { "id": 777898, "username": "Mahir Nozinovic", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/mahir_nozinovic", "type": "text/html" } } } }, "data": { "key": "MAWWPVGZ", "version": 1, "parentItem": "XPXZ5665", "itemType": "attachment", "linkMode": "linked_url", "title": "IEEE Xplore Full Text PDF", "accessDate": "2011-10-31T14:16:57Z", "url": "http://ieeexplore.ieee.org/ielx3/4821/13322/00609410.pdf?tp=&arnumber=609410&isnumber=13322", "note": "", "contentType": "application/pdf", "charset": "", "tags": [], "relations": {}, "dateAdded": "2011-10-31T14:16:57Z", "dateModified": "2011-10-31T14:16:57Z" } }, { "key": "XPXZ5665", "version": 1, "library": { "type": "group", "id": 56888, "name": "image series segmentation", "links": { "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/56888/items/XPXZ5665", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation/items/XPXZ5665", "type": "text/html" } }, "meta": { "createdByUser": { "id": 777898, "username": "Mahir Nozinovic", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/mahir_nozinovic", "type": "text/html" } } }, "creatorSummary": "Comaniciu and Meer", "parsedDate": "1997-06-17", "numChildren": 1 }, "data": { "key": "XPXZ5665", "version": 1, "itemType": "conferencePaper", "title": "Robust analysis of feature spaces: color image segmentation", "creators": [ { "creatorType": "author", "firstName": "D.", "lastName": "Comaniciu" }, { "creatorType": "author", "firstName": "P.", "lastName": "Meer" } ], "abstractNote": "A general technique for the recovery of significant image features is presented. The technique is based on the mean shift algorithm, a simple nonparametric procedure for estimating density gradients. Drawbacks of the current methods (including robust clustering) are avoided. Feature space of any nature can be processed, and as an example, color image segmentation is discussed. The segmentation is completely autonomous, only its class is chosen by the user. Thus, the same program can produce a high quality edge image, or provide, by extracting all the significant colors, a preprocessor for content-based query systems. A 512×512 color image is analyzed in less than 10 seconds on a standard workstation. Gray level images are handled as color images having only the lightness coordinate", "proceedingsTitle": ", 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1997. Proceedings", "conferenceName": ", 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1997. 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Google scholar only returns PDFs for this paper (which cannot be linked to the shared library).

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"A new color image segmentation algorithm using the concept of histon, based on Rough-set theory, is presented in this paper. The histon is an encrustation of histogram such that the elements in the histon are the set of all the pixels that can be classified as possibly belonging to the same segment. In rough-set theoretic sense, the histogram correlates with the lower approximation and the histon correlates with upper approximation. The roughness measure at every intensity level is calculated and then a thresholding method is applied for image segmentation. The proposed approach is compared with the histogram-based approach and the histon based approach. The experimental results demonstrate that the proposed approach yields better segmentation.", "publicationTitle": "Pattern Recognition Letters", "publisher": "", "place": "", "date": "March 1, 2008", "volume": "29", "issue": "4", "section": "", "partNumber": "", "partTitle": "", "pages": "483-493", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1016/j.patrec.2007.10.026", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S0167865507003595", "accessDate": "2011-10-26T13:23:02Z", "PMID": "", "PMCID": "", "ISSN": "0167-8655", "archive": "", "archiveLocation": "", "shortTitle": "Color image segmentation", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Histogram", "type": 1 }, { "tag": "Histon", "type": 1 }, { "tag": "Rough set", "type": 1 }, { "tag": "Segmentation", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2011-10-26T13:23:02Z", "dateModified": "2011-10-26T13:23:02Z" } }, { "key": "K5WSMH4N", "version": 1, "library": { "type": "group", "id": 56888, "name": "image series segmentation", "links": { "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/56888/items/K5WSMH4N", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation/items/K5WSMH4N", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/56888/items/IE5TFHCI", "type": "application/json" } }, "meta": { "createdByUser": { "id": 777898, "username": "Mahir Nozinovic", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/mahir_nozinovic", "type": "text/html" } } } }, "data": { "key": "K5WSMH4N", "version": 1, "parentItem": "IE5TFHCI", "itemType": "attachment", "linkMode": "linked_url", "title": "ScienceDirect Full Text PDF", "accessDate": "2011-10-26T13:22:33Z", "url": "http://www.sciencedirect.com/science?_ob=MiamiImageURL&_cid=272144&_user=1026342&_pii=S1566253511000510&_check=y&_origin=&_coverDate=31-Jul-2011&view=c&wchp=dGLzVlt-zSkWz&md5=f4ae820d8bb9d2237383bdf518598c12/1-s2.0-S1566253511000510-main.pdf", "note": "", "contentType": "application/pdf", "charset": "", "tags": [], "relations": {}, "dateAdded": "2011-10-26T13:22:33Z", "dateModified": "2011-10-26T13:22:33Z" } }, { "key": "SAPRII5W", "version": 1, "library": { "type": "group", "id": 56888, "name": "image series segmentation", "links": { "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/56888/items/SAPRII5W", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation/items/SAPRII5W", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/56888/items/IE5TFHCI", "type": "application/json" } }, "meta": { "createdByUser": { "id": 777898, "username": "Mahir Nozinovic", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/mahir_nozinovic", "type": "text/html" } } } }, "data": { "key": "SAPRII5W", "version": 1, "parentItem": "IE5TFHCI", "itemType": "attachment", "linkMode": "linked_url", "title": "ScienceDirect Snapshot", "accessDate": "2011-10-26T13:22:33Z", "url": "http://www.sciencedirect.com/science/article/pii/S1566253511000510", "note": "", "contentType": "text/html", "charset": "", "tags": [], "relations": {}, "dateAdded": "2011-10-26T13:22:33Z", "dateModified": "2011-10-26T13:22:33Z" } }, { "key": "IE5TFHCI", "version": 1, "library": { "type": "group", "id": 56888, "name": "image series segmentation", "links": { "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/56888/items/IE5TFHCI", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation/items/IE5TFHCI", "type": "text/html" } }, "meta": { "createdByUser": { "id": 777898, "username": "Mahir Nozinovic", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/mahir_nozinovic", "type": "text/html" } } }, "creatorSummary": "Li et al.", "numChildren": 2 }, "data": { "key": "IE5TFHCI", "version": 1, "itemType": "journalArticle", "title": "Image matting for fusion of multi-focus images in dynamic scenes", "creators": [ { "creatorType": "author", "firstName": "Shutao", "lastName": "Li" }, { "creatorType": "author", "firstName": "Xudong", "lastName": "Kang" }, { "creatorType": "author", "firstName": "Jianwen", "lastName": "Hu" }, { "creatorType": "author", "firstName": "Bin", "lastName": "Yang" } ], "abstractNote": "In this paper, we address the problem of fusing multi-focus images in dynamic scenes. The proposed approach consists of three main steps: first, the focus information of each source image obtained by morphological filtering is used to get the rough segmentation result which is one of the inputs of image matting. Then, image matting technique is applied to obtain the accurate focused region of each source image. Finally, the focused regions are combined together to construct the fused image. Through image matting, the proposed fusion algorithm combines the focus information and the correlations between nearby pixels together, and therefore tends to obtain more accurate fusion result. Experimental results demonstrate the superiority of the proposed method over traditional multi-focus image fusion methods, especially for those images in dynamic scenes.", "publicationTitle": "Information Fusion", "publisher": "", "place": "", "date": "", "volume": "", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1016/j.inffus.2011.07.001", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S1566253511000510", "accessDate": "2011-10-26T13:22:33Z", "PMID": "", "PMCID": "", "ISSN": "1566-2535", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Dynamic scenes", "type": 1 }, { "tag": "Focus information", "type": 1 }, { "tag": "Image matting", "type": 1 }, { "tag": "Morphological filtering", "type": 1 }, { "tag": "Multi-focus image fusion", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2011-10-26T13:22:33Z", "dateModified": "2011-10-26T13:22:33Z" } }, { "key": "H92AE8MD", "version": 1, "library": { "type": "group", "id": 56888, "name": "image series segmentation", "links": { "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/56888/items/H92AE8MD", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation/items/H92AE8MD", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/56888/items/PE6ITKF9", "type": "application/json" } }, "meta": { "createdByUser": { "id": 777898, "username": "Mahir Nozinovic", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/mahir_nozinovic", "type": "text/html" } } } }, "data": { "key": "H92AE8MD", "version": 1, "parentItem": "PE6ITKF9", "itemType": "attachment", "linkMode": "linked_url", "title": "IEEE Xplore Full Text PDF", "accessDate": "2011-10-26T13:14:21Z", "url": "http://ieeexplore.ieee.org/ielx5/34/5735600/05557884.pdf?tp=&arnumber=5557884&isnumber=5735600", "note": "", "contentType": "application/pdf", "charset": "", "tags": [], "relations": {}, "dateAdded": "2011-10-26T13:14:21Z", "dateModified": "2011-10-26T13:14:21Z" } }, { "key": "PE6ITKF9", "version": 1, "library": { "type": "group", "id": 56888, "name": "image series segmentation", "links": { "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/56888/items/PE6ITKF9", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation/items/PE6ITKF9", "type": "text/html" } }, "meta": { "createdByUser": { "id": 777898, "username": "Mahir Nozinovic", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/mahir_nozinovic", "type": "text/html" } } }, "creatorSummary": "Arbeláez et al.", "parsedDate": "2011-05", "numChildren": 1 }, "data": { "key": "PE6ITKF9", "version": 1, "itemType": "journalArticle", "title": "Contour Detection and Hierarchical Image Segmentation", "creators": [ { "creatorType": "author", "firstName": "P.", "lastName": "Arbeláez" }, { "creatorType": "author", "firstName": "M.", "lastName": "Maire" }, { "creatorType": "author", "firstName": "C.", "lastName": "Fowlkes" }, { "creatorType": "author", "firstName": "J.", "lastName": "Malik" } ], "abstractNote": "This paper investigates two fundamental problems in computer vision: contour detection and image segmentation. We present state-of-the-art algorithms for both of these tasks. Our contour detector combines multiple local cues into a globalization framework based on spectral clustering. Our segmentation algorithm consists of generic machinery for transforming the output of any contour detector into a hierarchical region tree. In this manner, we reduce the problem of image segmentation to that of contour detection. Extensive experimental evaluation demonstrates that both our contour detection and segmentation methods significantly outperform competing algorithms. The automatically generated hierarchical segmentations can be interactively refined by user-specified annotations. Computation at multiple image resolutions provides a means of coupling our system to recognition applications.", "publicationTitle": "IEEE Transactions on Pattern Analysis and Machine Intelligence", "publisher": "", "place": "", "date": "May 2011", "volume": "33", "issue": "5", "section": "", "partNumber": "", "partTitle": "", "pages": "898-916", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1109/TPAMI.2010.161", "citationKey": "", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "0162-8828", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "English", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Benchmark testing", "type": 1 }, { "tag": "Computer vision", "type": 1 }, { "tag": "Contour detection", "type": 1 }, { "tag": "Detectors", "type": 1 }, { "tag": "Histograms", "type": 1 }, { "tag": "Humans", "type": 1 }, { "tag": "Image edge detection", "type": 1 }, { "tag": "Image segmentation", "type": 1 }, { "tag": "Pixel", "type": 1 }, { "tag": "computer vision.", "type": 1 }, { "tag": "edge detection", "type": 1 }, { "tag": "hierarchical image segmentation", "type": 1 }, { "tag": "hierarchical region tree", "type": 1 }, { "tag": "object detection", "type": 1 }, { "tag": "pattern clustering", "type": 1 }, { "tag": "spectral clustering", "type": 1 }, { "tag": "trees (mathematics)", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2011-10-26T13:14:21Z", "dateModified": "2011-10-26T13:14:21Z" } }, { "key": "HEG5TBKJ", "version": 1, "library": { "type": "group", "id": 56888, "name": "image series segmentation", "links": { "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/56888/items/HEG5TBKJ", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation/items/HEG5TBKJ", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/56888/items/59ER4JTS", "type": "application/json" } }, "meta": { "createdByUser": { "id": 777898, "username": "Mahir Nozinovic", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/mahir_nozinovic", "type": "text/html" } } }, "numChildren": 0 }, "data": { "key": "HEG5TBKJ", "version": 1, "parentItem": "59ER4JTS", "itemType": "note", "note": "

Google scholar only returns PDFs for this paper.

", "tags": [], "relations": {}, "dateAdded": "2011-10-26T13:13:07Z", "dateModified": "2011-10-26T13:13:07Z" } }, { "key": "8WH24DNM", "version": 1, "library": { "type": "group", "id": 56888, "name": "image series segmentation", "links": { "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/56888/items/8WH24DNM", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/image_series_segmentation/items/8WH24DNM", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/56888/items/WM4TDDAH", "type": "application/json" } }, "meta": { "createdByUser": { "id": 777898, "username": "Mahir Nozinovic", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/mahir_nozinovic", "type": "text/html" } } }, "numChildren": 0 }, "data": { "key": "8WH24DNM", "version": 1, "parentItem": "WM4TDDAH", "itemType": "note", "note": "

This is the only result google scholar returns for this paper.

", "tags": [], "relations": {}, "dateAdded": "2011-10-26T13:09:09Z", "dateModified": "2011-10-26T13:09:49Z" } } ]