Water reflection recognition based on motion blur invariant moments in curvelet space

Water reflection, a typical imperfect reflection symmetry problem, plays an important role in image content analysis. Existing techniques of symmetry recognition, however, cannot recognize water reflection images correctly because of the complex and various distortions caused by the water wave. Henc...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 22(2013), 11 vom: 15. Nov., Seite 4301-13
1. Verfasser: Zhong, Sheng-Hua (VerfasserIn)
Weitere Verfasser: Liu, Yan, Liu, Yang, Li, Chang-Sheng
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2013
Zugriff auf das übergeordnete Werk:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:Journal Article Research Support, Non-U.S. Gov't Water 059QF0KO0R
LEADER 01000naa a22002652 4500
001 NLM229092284
003 DE-627
005 20231224081405.0
007 cr uuu---uuuuu
008 231224s2013 xx |||||o 00| ||eng c
024 7 |a 10.1109/TIP.2013.2271851  |2 doi 
028 5 2 |a pubmed24n0763.xml 
035 |a (DE-627)NLM229092284 
035 |a (NLM)23846471 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Zhong, Sheng-Hua  |e verfasserin  |4 aut 
245 1 0 |a Water reflection recognition based on motion blur invariant moments in curvelet space 
264 1 |c 2013 
336 |a Text  |b txt  |2 rdacontent 
337 |a ƒaComputermedien  |b c  |2 rdamedia 
338 |a ƒa Online-Ressource  |b cr  |2 rdacarrier 
500 |a Date Completed 14.04.2014 
500 |a Date Revised 19.09.2013 
500 |a published: Print-Electronic 
500 |a Citation Status MEDLINE 
520 |a Water reflection, a typical imperfect reflection symmetry problem, plays an important role in image content analysis. Existing techniques of symmetry recognition, however, cannot recognize water reflection images correctly because of the complex and various distortions caused by the water wave. Hence, we propose a novel water reflection recognition technique to solve the problem. First, we construct a novel feature space composed of motion blur invariant moments in low-frequency curvelet space and of curvelet coefficients in high-frequency curvelet space. Second, we propose an efficient algorithm including two sub-algorithms: low-frequency reflection cost minimization and high-frequency curvelet coefficients discrimination to classify water reflection images and to determine the reflection axis. Through experimenting on authentic images in a series of tasks, the proposed techniques prove effective and reliable in classifying water reflection images and detecting the reflection axis, as well as in retrieving images with water reflection 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
650 7 |a Water  |2 NLM 
650 7 |a 059QF0KO0R  |2 NLM 
700 1 |a Liu, Yan  |e verfasserin  |4 aut 
700 1 |a Liu, Yang  |e verfasserin  |4 aut 
700 1 |a Li, Chang-Sheng  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society  |d 1992  |g 22(2013), 11 vom: 15. Nov., Seite 4301-13  |w (DE-627)NLM09821456X  |x 1941-0042  |7 nnns 
773 1 8 |g volume:22  |g year:2013  |g number:11  |g day:15  |g month:11  |g pages:4301-13 
856 4 0 |u http://dx.doi.org/10.1109/TIP.2013.2271851  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 22  |j 2013  |e 11  |b 15  |c 11  |h 4301-13