{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T20:38:01Z","timestamp":1771706281803,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2015,5,13]],"date-time":"2015-05-13T00:00:00Z","timestamp":1431475200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Segmentation, which is usually the first step in object-based image analysis (OBIA), greatly influences the quality of final OBIA results. In many existing multi-scale segmentation algorithms, a common problem is that under-segmentation and over-segmentation always coexist at any scale. To address this issue, we propose a new method that integrates the newly developed constrained spectral variance difference (CSVD) and the edge penalty (EP). First, initial segments are produced by a fast scan. Second, the generated segments are merged via a global mutual best-fitting strategy using the CSVD and EP as merging criteria. Finally, very small objects are merged with their nearest neighbors to eliminate the remaining noise. A series of experiments based on three sets of remote sensing images, each with different spatial resolutions, were conducted to evaluate the effectiveness of the proposed method. Both visual and quantitative assessments were performed, and the results show that large objects were better preserved as integral entities while small objects were also still effectively delineated. The results were also found to be superior to those from eCongnition\u2019s multi-scale segmentation.<\/jats:p>","DOI":"10.3390\/rs70505980","type":"journal-article","created":{"date-parts":[[2015,5,13]],"date-time":"2015-05-13T12:42:07Z","timestamp":1431520927000},"page":"5980-6004","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":47,"title":["Image Segmentation Based on Constrained Spectral Variance Difference and Edge Penalty"],"prefix":"10.3390","volume":"7","author":[{"given":"Bo","family":"Chen","sequence":"first","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing100101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fang","family":"Qiu","sequence":"additional","affiliation":[{"name":"Geospatial Information Sciences, University of Texas at Dallas, Dallas, TX 75080, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5546-365X","authenticated-orcid":false,"given":"Bingfang","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing100101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongyue","family":"Du","sequence":"additional","affiliation":[{"name":"China Mapping Technology Service Corporation, Beijing 100088, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2015,5,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2025","DOI":"10.1080\/014311698214848","article-title":"Synergy in remote sensing\u2014What\u2019s in a pixel?","volume":"19","author":"Cracknell","year":"1998","journal-title":"Int. J. Remote Sens."},{"key":"ref_2","first-page":"12","article-title":"What\u2019s wrong with pixels? Some recent developments interfacing remote sensing and GIS","volume":"6","author":"Blaschke","year":"2001","journal-title":"GeoBIT\/GIS"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/S0304-3800(03)00139-X","article-title":"A multi-scale segmentation\/object relationship modelling methodology for landscape analysis","volume":"168","author":"Burnett","year":"2003","journal-title":"Ecol. Model."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Blaschke, T., Lang, S., and Hay, G. (2008). Object Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications, Springer. 1st ed.","DOI":"10.1007\/978-3-540-77058-9"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.isprsjprs.2009.06.004","article-title":"Object based image analysis for remote sensing","volume":"63","author":"Blaschke","year":"2010","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/S0734-189X(85)90153-7","article-title":"Survey: Image segmentation techniques","volume":"29","author":"Haralick","year":"1985","journal-title":"Comput. Vis. Graph. Image Process."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1277","DOI":"10.1016\/0031-3203(93)90135-J","article-title":"A review on image segmentation techniques","volume":"26","author":"Pal","year":"1993","journal-title":"Pattern Recognit."},{"key":"ref_8","first-page":"211","article-title":"New contextual approaches using image segmentation for object-based classification","volume":"Volume 5","year":"2004","journal-title":"Remote Sensing Image Analysis: Including the Spatial Domain"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1006\/cviu.1993.1024","article-title":"A review of recent texture segmentation and feature extraction techniques","volume":"57","author":"Reed","year":"1993","journal-title":"Comput. Vis. Graph. Image Process."},{"key":"ref_10","first-page":"380","article-title":"Segmentation of high-resolution remotely sensed data- concepts, applications and problems","volume":"34","author":"Schiewe","year":"2002","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_11","unstructured":"Wagner, W., and Sz\u00e9kely, B. (2010, January 5\u20137). A review on image segmentation techniques with remote sensing perspective. Proceedings of the ISPRS TC VII Symposium\u2014100 Years ISPRS, Vienna, Austria."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"776","DOI":"10.1109\/TIP.2010.2076298","article-title":"HAIRIS: A method for automatic image registration through histogram-based image segmentation","volume":"20","year":"2011","journal-title":"IEEE Trans. Image Process."},{"key":"ref_13","unstructured":"Cocquerez, J.P., and Philipp, S. (1995). Analyse D\u2019images: Filtrage et Segmentation, Masson."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1109\/34.87344","article-title":"Watershed in digital spaces: An efficient algorithm based on immersion simulations","volume":"13","author":"Vincent","year":"1991","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_15","unstructured":"Debeir, O. (2001). Segmentation Supervis\u00e9e d\u2019Images. [Ph.D. Thesis, Facult\u00e9 des Sciences Appliqu\u00e9es, Universit\u00e9 Libre de Bruxelles]."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1109\/TPAMI.1986.4767851","article-title":"A computational approach to edge detection","volume":"6","author":"Canny","year":"1986","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1285","DOI":"10.14358\/PERS.71.11.1285","article-title":"Assessment of very high spatial resolution satellite image segmentations","volume":"71","author":"Carleer","year":"2005","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_18","unstructured":"Jain, A.K. (1989). Fundamentals of Digital Image Processing, Prentice-Hall."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2043","DOI":"10.1016\/S0031-3203(97)00015-0","article-title":"A multiscale gradient algorithm for image segmentation using watersheds","volume":"30","author":"Wang","year":"1997","journal-title":"Pattern Recognit."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1145\/321941.321956","article-title":"Picture segmentation by a tree traversal algorithm","volume":"23","author":"Horowitz","year":"1976","journal-title":"J. ACM"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1109\/34.295913","article-title":"Seeded Region Growing","volume":"16","author":"Adams","year":"1994","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_22","unstructured":"Strobl, J., Blaschke, T., and Griesebner, G. (2000). Angewandte Geographische Informations-Verarbeitung XII, Beitr\u00e4ge zum AGIT-Symposium Salzbug, Salzbug, Austria, Herbert Wichmann Verlag."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1109\/34.49050","article-title":"Integrating region growing and edge detection","volume":"12","author":"Pavlidis","year":"1990","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_24","first-page":"485","article-title":"Image segmentation towards new image representation methods","volume":"6","author":"Cortez","year":"1995","journal-title":"Signal Process."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1684","DOI":"10.1109\/83.730380","article-title":"Hybrid image segmentation using watersheds and fast region merging","volume":"7","author":"Haris","year":"1998","journal-title":"IEEE Trans. Image Process."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"409","DOI":"10.14358\/PERS.74.4.409","article-title":"Size-constrained region merging (SCRM): An automated delineation tool for assisted photointerpretation","volume":"74","author":"Castilla","year":"2008","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2126","DOI":"10.1109\/TPAMI.2008.15","article-title":"IRGS: Image segmentation using edge penalties and region growing","volume":"30","author":"Yu","year":"2008","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.isprsjprs.2013.01.002","article-title":"Boundary-constrained multi-scale segmentation method for remote sensing images","volume":"78","author":"Zhang","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"71","DOI":"10.14358\/PERS.80.1.71","article-title":"Fast hierarchical segmentation of high-resolution remote sensing image with adaptive edge penalty","volume":"80","author":"Zhang","year":"2014","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_30","unstructured":"Robinson, D.J., Redding, N.J., and Crisp, D.J. (2002). Scientific and Technical Report, Defense Science and Technology Organization."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1080\/14498596.2010.487850","article-title":"Enhanced evaluation of image segmentation results","volume":"55","author":"Marpu","year":"2010","journal-title":"J. Spat. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/j.isprsjprs.2003.10.002","article-title":"Multiresolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information","volume":"58","author":"Benz","year":"2004","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1109\/34.16711","article-title":"Hierarchy in picture segmentation: A stepwise optimization approach","volume":"11","author":"Beaulieu","year":"1989","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_34","unstructured":"Saarinen, K. (1994, January 13\u201316). Color image segmentation by a watershed algorithm and region adjacency graph processing. Proceedings of the IEEE International Conference on Image Processing, Austin, TX, USA."},{"key":"ref_35","unstructured":"Chen, Z., Zhao, Z.M., Yan, D.M., and Chen, R.X. (2005, January 29). Multi-scale segmentation of the high resolution remote sensing image. Proceedings of the 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005, (IGARSS\u201905), Seoul, South Korea."},{"key":"ref_36","first-page":"312","article-title":"Edge-guided segmentation method for multiscale and high resolution remote sensing image","volume":"29","author":"Tan","year":"2010","journal-title":"J. Infrared Millim. Waves"},{"key":"ref_37","first-page":"1492","article-title":"Automated hierarchical segmentation of high-resolution remote sensing imagery with introduced relaxation factors","volume":"17","author":"Deng","year":"2013","journal-title":"J. Remote Sens."},{"key":"ref_38","unstructured":"Ballard, D., and Brown, C. (1982). Computer Vision, Prentice-Hall. [1st ed.]."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"808","DOI":"10.1109\/34.236248","article-title":"Adaptive split-and-merge segmentation based on piecewise least-square approximation","volume":"15","author":"Wu","year":"1993","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Kanungo, T., Dom, B., Niblack, W., and Steele, D. (1994, January 21\u201323). A fast algorithm for MDL-based multi-band image segmentation. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Seattle, WA, USA.","DOI":"10.1109\/CVPR.1994.323792"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2781","DOI":"10.1016\/S0031-3203(03)00170-5","article-title":"Perceptual grouping of segmented regions in color images","volume":"36","author":"Luo","year":"2003","journal-title":"Pattern Recognit."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1920","DOI":"10.1109\/TGRS.2005.852080","article-title":"Markov random field on region adjacency graph for the fusion of SAR and optical data in radar grammetric applications","volume":"43","author":"Tupin","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","unstructured":"Xiao, P., Feng, X.Z., Wang, P., Ye, S., Wu, G., Wang, K., and Feng, X.L. (2012). High Resolution Remote Sensing Image Segmentation and Information Extraction, Science Press. [1st ed.]."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"801","DOI":"10.1109\/83.841527","article-title":"A simple unsupervised MRF model based image segmentation approach","volume":"9","author":"Sarkar","year":"2000","journal-title":"IEEE Trans. Image Process."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1335","DOI":"10.1016\/0031-3203(95)00169-7","article-title":"A survey on evaluation methods for image segmentation","volume":"29","author":"Zhang","year":"1996","journal-title":"Pattern Recognit."},{"key":"ref_46","unstructured":"Lucieer, A. (2004). Uncertainties in Segmentation and Their Visualization. [Ph.D. Thesis, Utrecht University]. ITC Dissertation 113, Enschede."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/5\/5980\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:46:16Z","timestamp":1760215576000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/5\/5980"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,5,13]]},"references-count":46,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2015,5]]}},"alternative-id":["rs70505980"],"URL":"https:\/\/doi.org\/10.3390\/rs70505980","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,5,13]]}}}