{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T15:08:58Z","timestamp":1761664138937,"version":"3.37.3"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T00:00:00Z","timestamp":1602460800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T00:00:00Z","timestamp":1602460800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772319","61773244","61976125","61976124"],"award-info":[{"award-number":["61772319","61773244","61976125","61976124"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,2]]},"DOI":"10.1007\/s11042-020-09908-0","type":"journal-article","created":{"date-parts":[[2020,10,12]],"date-time":"2020-10-12T07:02:55Z","timestamp":1602486175000},"page":"6143-6169","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Image matting trimap optimization by ant colony algorithm"],"prefix":"10.1007","volume":"80","author":[{"given":"Genji","family":"Yuan","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2080-8678","authenticated-orcid":false,"given":"Jinjiang","family":"Li","sequence":"additional","affiliation":[]},{"given":"Zhen","family":"Hua","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,10,12]]},"reference":[{"issue":"11","key":"9908_CR1","doi-asserted-by":"publisher","first-page":"2274","DOI":"10.1109\/TPAMI.2012.120","volume":"34","author":"R Achanta","year":"2012","unstructured":"Achanta R, Shaji A, Smith K, Lucchi A, Fua P, S\u00fcsstrunk Sabine (2012) SLIC Superpixels compared to state-of-the-art superpixel methods. IEEE Transactions on Pattern Analysis and Machine Intelligence 34(11):2274\u20132282","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"9908_CR2","doi-asserted-by":"crossref","unstructured":"Aksoy Y, Aydin TO, Pollefeys M (2017) Designing effective Inter-Pixel information flow for natural image matting. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 228\u2013236","DOI":"10.1109\/CVPR.2017.32"},{"key":"9908_CR3","doi-asserted-by":"crossref","unstructured":"Chao D, Chen CL, He K, Tang X (2014) Learning a deep convolutional network for image super-resolution. In: European Conference on Computer Vision, pp 184\u2013199","DOI":"10.1007\/978-3-319-10593-2_13"},{"issue":"9","key":"9908_CR4","doi-asserted-by":"publisher","first-page":"2175","DOI":"10.1109\/TPAMI.2013.18","volume":"35","author":"Q Chen","year":"2013","unstructured":"Chen Q, Li D, Tang C-K (2013) KNN Matting. IEEE Transactions on Pattern Analysis and Machine Intelligence 35(9):2175\u20132188","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"6","key":"9908_CR5","first-page":"1","volume":"31","author":"X Chen","year":"2012","unstructured":"Chen X, Zou D, Zhao Q, Tan P (2012) Manifold preserving edit propagation. ACM Trans Graph 31(6):1\u20137","journal-title":"ACM Trans Graph"},{"key":"9908_CR6","doi-asserted-by":"crossref","unstructured":"Chen X, Zou D, Zhou SZ, Zhao Q, Tan P (2013) Image matting with local and nonlocal smooth priors. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 1902\u20131907","DOI":"10.1109\/CVPR.2013.248"},{"key":"9908_CR7","doi-asserted-by":"crossref","unstructured":"Cho D, Tai Y-W, Kweon I (2016) Natural image matting using deep convolutional neural networks. In: European Conference on Computer Vision, pp 626\u2013643","DOI":"10.1007\/978-3-319-46475-6_39"},{"key":"9908_CR8","unstructured":"Chuang Y, Curless B, Salesin DH, Szeliski R (2001) A bayesian approach to digital matting. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 264\u2013271"},{"issue":"2","key":"9908_CR9","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1111\/j.1467-8659.2009.01627.x","volume":"29","author":"ES Gastal","year":"2010","unstructured":"Gastal ES, Oliveira M (2010) Shared sampling for real-time alpha matting. Computer Graphics Forum 29(2):575\u2013584","journal-title":"Computer Graphics Forum"},{"key":"9908_CR10","unstructured":"Goodfellow I, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Bengio Y (2014) Generative adversarial nets. In: Advances in Neural Information Processing Systems, pp 2672\u20132680"},{"issue":"6","key":"9908_CR11","first-page":"1256","volume":"2","author":"C Gupta","year":"2013","unstructured":"Gupta C, Gupta S (2013) Edge detection of an image based on ant colony optimization technique. Int J Sci Res 2(6):1256\u20131260","journal-title":"Int J Sci Res"},{"key":"9908_CR12","doi-asserted-by":"crossref","unstructured":"He K, Rhemann C, Rother C, Tang X, Sun J (2011) A global sampling method for alpha matting. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 2049\u20132056","DOI":"10.1109\/CVPR.2011.5995495"},{"key":"9908_CR13","doi-asserted-by":"crossref","unstructured":"He K, Sun J, Tang X (2010) Fast matting using large kernel matting laplacian matrices. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 2165\u20132172","DOI":"10.1109\/CVPR.2010.5539896"},{"key":"9908_CR14","doi-asserted-by":"crossref","unstructured":"Hsieh CL, Lee MS (2013) [14]. Automatic trimap generation for digital image matting. In: Signal and Information Processing Association Annual Summit and Conference, pp 1\u20135","DOI":"10.1109\/APSIPA.2013.6694178"},{"issue":"8","key":"9908_CR15","doi-asserted-by":"publisher","first-page":"3739","DOI":"10.1109\/TIP.2019.2902830","volume":"28","author":"H Huang","year":"2019","unstructured":"Huang H, Liang Y, Yang X, Hao Z (2019) Pixel-level Discrete Multiobjective Sampling for Image Matting. IEEE Trans Image Process 28(8):3739\u20133751","journal-title":"IEEE Trans Image Process"},{"key":"9908_CR16","doi-asserted-by":"crossref","unstructured":"Jayoma JM, Gerardo BD, Medina RM (2018) Finding the shortest path using enhanced ant algorithm with path elimination rules. In: IEEE Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, pp 1\u20136","DOI":"10.1109\/HNICEM.2018.8666432"},{"issue":"9","key":"9908_CR17","doi-asserted-by":"publisher","first-page":"1896","DOI":"10.1109\/TMM.2016.2576283","volume":"18","author":"KR Jerripothula","year":"2016","unstructured":"Jerripothula KR, Cai J, Yuan J (2016) Image co-segmentation via saliency co-fusion. IEEE Transactions on Multimedia 18(9):1896\u20131909","journal-title":"IEEE Transactions on Multimedia"},{"issue":"9","key":"9908_CR18","doi-asserted-by":"publisher","first-page":"2466","DOI":"10.1109\/TMM.2018.2798294","volume":"20","author":"KR Jerripothula","year":"2018","unstructured":"Jerripothula KR, Cai J, Yuan J (2018) Quality-guided fusion-based co-saliency estimation for image co-segmentation and colocalization. IEEE Transactions on Multimedia 20(9):2466\u20132477","journal-title":"IEEE Transactions on Multimedia"},{"key":"9908_CR19","doi-asserted-by":"crossref","unstructured":"Jevti\u0107 A, Quintanilla-Dominguez J, Cortina-Januchs MG, Andina D (2009) Edge detection using ant colony search algorithm and multiscale contrast enhancement. In: Systems, Man and Cybernetics, pp 2193\u20132198","DOI":"10.1109\/ICSMC.2009.5345922"},{"key":"9908_CR20","doi-asserted-by":"crossref","unstructured":"Johnson J, Alahi A, Li FF (2016) Perceptual losses for Real-Time style transfer and Super-Resolution. In: European Conference on Computer Vision, pp 694\u2013711","DOI":"10.1007\/978-3-319-46475-6_43"},{"key":"9908_CR21","doi-asserted-by":"crossref","unstructured":"Kim J, Lee JK, Lee KM (2016) Accurate image Super-Resolution using very deep convolutional networks. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 1646\u20131654","DOI":"10.1109\/CVPR.2016.182"},{"key":"9908_CR22","doi-asserted-by":"crossref","unstructured":"Ledig C, Theis L, Husazr F, Caballero J, Cunningham A, Acosta A, Shi W (2016) Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. In: Computer Vision and Pattern Recognition, pp 4681\u20134690","DOI":"10.1109\/CVPR.2017.19"},{"key":"9908_CR23","doi-asserted-by":"crossref","unstructured":"Lee P, Wu Y (2011) Nonlocal matting. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 2193\u20132200","DOI":"10.1109\/CVPR.2011.5995665"},{"issue":"2","key":"9908_CR24","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1109\/TPAMI.2007.1177","volume":"30","author":"A Levin","year":"2008","unstructured":"Levin A, Lischinski D, Weiss Y (2008) A closed-form solution to natural image matting. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(2):228\u2013242","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"10","key":"9908_CR25","doi-asserted-by":"publisher","first-page":"1699","DOI":"10.1109\/TPAMI.2008.168","volume":"30","author":"A Levin","year":"2008","unstructured":"Levin A, Rav-Acha A, Lischinski D (2008) Spectral matting. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(10):1699\u20131712","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"9908_CR26","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.cviu.2017.06.011","volume":"162","author":"C Li","year":"2017","unstructured":"Li C, Wang P, Zhu X, Pi H (2017) Three-layer graph framework with the sumD feature for alpha matting. Comput Vis Image Underst 162:34\u201345","journal-title":"Comput Vis Image Underst"},{"key":"9908_CR27","doi-asserted-by":"crossref","unstructured":"Lim B, Son S, Kim H, Nah S, Lee KM (2017) Enhanced deep residual networks for single image Super-Resolution. In: IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp 136\u2013144","DOI":"10.1109\/CVPRW.2017.151"},{"key":"9908_CR28","unstructured":"Lutz S, Amplianitis K, Smolic A (2018) AlphaGAN:, Generative adversarial networks for natural image matting. arXiv:1807.10088"},{"issue":"7","key":"9908_CR29","doi-asserted-by":"publisher","first-page":"623","DOI":"10.1007\/s00500-005-0511-y","volume":"10","author":"H Nezamabadi-Pour","year":"2006","unstructured":"Nezamabadi-Pour H, Saryazdi S, Rashedi E (2006) Edge detection using ant algorithms. Soft Comput 10(7):623\u2013628","journal-title":"Soft Comput"},{"issue":"2","key":"9908_CR30","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1177\/0165551516638784","volume":"43","author":"A Onan","year":"2017","unstructured":"Onan A, Bulut H, Korukoglu S (2017) An improved ant algorithm with LDA-based representation for text document clustering. J Inf Sci 43 (2):275\u2013292","journal-title":"J Inf Sci"},{"key":"9908_CR31","unstructured":"Radford A, Metz L, Chintala SJAPA (2015) Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv:1511.06434"},{"key":"9908_CR32","doi-asserted-by":"crossref","unstructured":"Rhemann C, Rother C, Gelautz M (2008) Improving color modeling for alpha matting, In: British Machine Vision Conference, pp 1155\u20131164","DOI":"10.5244\/C.22.115"},{"key":"9908_CR33","doi-asserted-by":"crossref","unstructured":"Rhemann C, Rother C, Wang J, Gelautz M, Kohli P, Rott P (2009) A perceptually motivated online benchmark for image matting. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 1826\u20131833","DOI":"10.1109\/CVPRW.2009.5206503"},{"key":"9908_CR34","doi-asserted-by":"crossref","unstructured":"R\u00fcnz M, Agapito L (2017) Co-fusion: Real-time segmentation, tracking and fusion of multiple objects. In: IEEE Conference on Robotics and Automation, pp 4471\u20134478","DOI":"10.1109\/ICRA.2017.7989518"},{"key":"9908_CR35","doi-asserted-by":"crossref","unstructured":"Sajjadi MSM, Sch\u00f6lkopf B, Hirsch M (2016) Enhancenet: Single Image Super-Resolution through Automated Texture Synthesis. In: International Conference on Computer Vision, pp 4491\u20134500","DOI":"10.1109\/ICCV.2017.481"},{"issue":"4","key":"9908_CR36","doi-asserted-by":"publisher","first-page":"625","DOI":"10.1007\/s11760-013-0569-4","volume":"8","author":"G Samit","year":"2014","unstructured":"Samit G, Kumar D, Mohanty PJSI, Processing VK (2014) Edge detection using ACO and F ratio. Image and Video Processing 8(4):625\u2013634","journal-title":"Image and Video Processing"},{"key":"9908_CR37","doi-asserted-by":"crossref","unstructured":"Shahrian E, Rajan D (2012) Weighted color and texture sample selection for image matting. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 718\u2013725","DOI":"10.1109\/CVPR.2012.6247741"},{"key":"9908_CR38","doi-asserted-by":"crossref","unstructured":"Shahrian E, Rajan D, Price B, Cohen S (2013) Improving image matting using comprehensive sampling sets. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 636\u2013643","DOI":"10.1109\/CVPR.2013.88"},{"key":"9908_CR39","doi-asserted-by":"crossref","unstructured":"Shen X, Tao X, Gao H, Zhou C, Jia J (2016) Deep automatic portrait matting. In: European Conference on Computer Vision, pp 92\u2013107","DOI":"10.1007\/978-3-319-46448-0_6"},{"issue":"3","key":"9908_CR40","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1145\/1015706.1015721","volume":"23","author":"J Sun","year":"2004","unstructured":"Sun J, Jia J, Tang CK, Shum HY (2004) Poisson matting. ACM Trans Graph 23(3):315\u2013321","journal-title":"ACM Trans Graph"},{"key":"9908_CR41","doi-asserted-by":"crossref","unstructured":"Szegedy C, Ioffe S, Vanhoucke V, Alemi AA (2017) Inception-v4, inception-resnet and the impact of residual connections on learning. Thirty-First AAAI Conference on Artificial Intelligence, arXiv preprint arXiv:1602:07261","DOI":"10.1609\/aaai.v31i1.11231"},{"key":"9908_CR42","unstructured":"Tian J, Yu W, Xie S (2008) An ant colony optimization algorithm for image edge detection. In: Evol Comput, pp 751\u2013756"},{"key":"9908_CR43","doi-asserted-by":"crossref","unstructured":"Wang J, Cohen MF (2007) Optimized color sampling for robust matting. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 1\u20138","DOI":"10.1109\/CVPR.2007.383006"},{"issue":"2","key":"9908_CR44","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1561\/0600000019","volume":"3","author":"J Wang","year":"2008","unstructured":"Wang J, Cohen MF (2008) Image and video matting: a survey. Foundations and Trends in Computer Graphics and Vision 3(2):97\u2013175","journal-title":"Foundations and Trends in Computer Graphics and Vision"},{"key":"9908_CR45","doi-asserted-by":"crossref","unstructured":"Wang Z, Ding L, Yang J, Wei H, Huang T (2015) Deep networks for image Super-Resolution with sparse prior. In: IEEE Conference on Computer Vision, pp 370\u2013378","DOI":"10.1109\/ICCV.2015.50"},{"key":"9908_CR46","doi-asserted-by":"crossref","unstructured":"Wang X, Li S, Sui L, Wang J (2019) Quick automatic head image matting method based on segmentation and propagation, Patern Recognition Letters 130: 30\u201337","DOI":"10.1016\/j.patrec.2019.02.012"},{"key":"9908_CR47","doi-asserted-by":"crossref","unstructured":"Wang X, Yu K, Dong C, Change Loy C (2018) Recovering realistic texture in image super-resolution by deep spatial feature transform. In: Computer Vision and Pattern Recognition, pp 606\u2013615","DOI":"10.1109\/CVPR.2018.00070"},{"key":"9908_CR48","doi-asserted-by":"crossref","unstructured":"Wang X, et al. (2018) \u201cESRGAN: Enhanced Super-resolution generative adversarial networks.\u201d In: European Conference on Computer Vision, pp 63\u201379","DOI":"10.1007\/978-3-030-11021-5_5"},{"key":"9908_CR49","doi-asserted-by":"crossref","unstructured":"Xie J, Cai J (2015) An ant colony algorithm on continuous searching space, Parallel In: International Symposium on Multispectral Image Processing and Pattern Recognition, pp 9814\u20139816","DOI":"10.1117\/12.2205216"},{"key":"9908_CR50","doi-asserted-by":"crossref","unstructured":"Xu N, Price BL, Cohen S, Huang TS (2017) Deep Image Matting. arXiv:1703.03872","DOI":"10.1109\/CVPR.2017.41"},{"key":"9908_CR51","doi-asserted-by":"crossref","unstructured":"Zhang Y, Tian Y, Yu K, Zhong B, Yun F (2018) Residual dense network for image Super-Resolution. In: IEEE Conference on Computer Vision and Pattern Recognition., pp 2472\u20132481","DOI":"10.1109\/CVPR.2018.00262"},{"key":"9908_CR52","unstructured":"Zheng Y, Kambhamettu C (2009) Learning based digital matting. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 889\u2013896"},{"key":"9908_CR53","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/j.neucom.2018.02.027","volume":"290","author":"F Zhou","year":"2018","unstructured":"Zhou F, Li X, Li ZJN (2018) High-frequency details enhancing DenseNet for super-resolution. Neurocomputing 290:34\u201342","journal-title":"Neurocomputing"},{"key":"9908_CR54","unstructured":"Zhuang X (2004) Edge feature extraction in digital images with the ant colony system, IEEE Conference on Computational Intelligence for Measurement Systems and Applications, pp 133\u2013136"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09908-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-020-09908-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09908-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,22]],"date-time":"2022-11-22T23:22:05Z","timestamp":1669159325000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-020-09908-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,12]]},"references-count":54,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2021,2]]}},"alternative-id":["9908"],"URL":"https:\/\/doi.org\/10.1007\/s11042-020-09908-0","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2020,10,12]]},"assertion":[{"value":"19 March 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 August 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 September 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 October 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}