dc.contributor.author | Οικονομόπουλος, Θεόδωρος Λ. | el |
dc.contributor.author | Ασβεστάς, Παντελής Α. | el |
dc.contributor.author | Ματσόπουλος, Γεώργιος Κ. | el |
dc.date.accessioned | 2015-02-08T18:08:28Z | |
dc.date.issued | 2015-02-08 | |
dc.identifier.uri | http://hdl.handle.net/11400/5867 | |
dc.rights | Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.source | http://ieeexplore.ieee.org/ | en |
dc.subject | Image enhancement | |
dc.subject | Image segmentation | |
dc.subject | Βελτίωση εικόνας | |
dc.subject | Κατάτμηση εικόνας | |
dc.title | Regional partitioned iterated function systems for digital image enhancement | en |
heal.type | conferenceItem | |
heal.generalDescription | Proceedings | en |
heal.classification | Medicine | |
heal.classification | Biomedical engineering | |
heal.classification | Ιατρική | |
heal.classification | Βιοϊατρική τεχνολογία | |
heal.classificationURI | http://id.loc.gov/authorities/subjects/sh00006614 | |
heal.classificationURI | http://id.loc.gov/authorities/subjects/sh85014237 | |
heal.classificationURI | **N/A**-Ιατρική | |
heal.classificationURI | **N/A**-Βιοϊατρική τεχνολογία | |
heal.identifier.secondary | DOI: 10.1109/IPTA.2012.6469514 | |
heal.dateAvailable | 10000-01-01 | |
heal.language | en | |
heal.access | forever | |
heal.recordProvider | Τ.Ε.Ι. Αθήνας. Σχολή Τεχνολογικών Εφαρμογών. Τμήμα Μηχανικών Βιοϊατρικής Τεχνολογίας Τ.Ε. | el |
heal.publicationDate | 2012 | |
heal.bibliographicCitation | Economopoulos, T., Asvestas, P. and Matsopoulos, G. (2012). Regional partitioned iterated function systems for digital image enhancement. In the 3rd International Conference on Image Processing Theory, Tools and Applications. Istanbul, 15th-18th October 2012. pp. 265-269. IEEE. | en |
heal.abstract | A new technique is presented for enhancing the contrast of digital images. The proposed method is based on the regional application of the Partitioned Iterated Function Systems (PIFS) algorithm. The subject image is partitioned into domain regions, using a standard Region Growing approach. Each domain region is further partitioned into smaller range regions. In turn, each range region is transformed through a contractive affine spatial transform, as well as through a linear transform of the gray levels of its pixels. The PIFS is used in order to create a lowpass version of the original image, after processing each region. The contrast-enhanced image is obtained by adding the difference of the original image with its lowpass version, to the original image itself. The quantitative and qualitative results obtained, show that the proposed method achieves higher quality image enhancement, compared to two widely used contrast enhancement techniques. | en |
heal.publisher | IEEE | en |
heal.fullTextAvailability | true | |
heal.conferenceName | International Conference on Image Processing Theory, Tools and Applications | en |
heal.conferenceItemType | full paper |
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