DocumentCode :
3061858
Title :
Surface projection for mixed pixel restoration
Author :
Larkins, Robert L. ; Cree, Michael J. ; Dorrington, Adrian A. ; Godbaz, John P.
Author_Institution :
Dept. of Eng., Univ. of Waikato, Hamilton, New Zealand
fYear :
2009
fDate :
23-25 Nov. 2009
Firstpage :
431
Lastpage :
436
Abstract :
Amplitude modulated full-field range-imagers are measurement devices that determine the range to an object simultaneously for each pixel in the scene, but due to the nature of this operation, they commonly suffer from the significant problem of mixed pixels. Once mixed pixels are identified a common procedure is to remove them from the scene; this solution is not ideal as the captured point cloud may become damaged. This paper introduces an alternative approach, in which mixed pixels are projected onto the surface that they should belong. This is achieved by breaking the area around an identified mixed pixel into two classes. A parametric surface is then fitted to the class closest to the mixed pixel, with this mixed pixel then being project onto this surface. The restoration procedure was tested using twelve simulated scenes designed to determine its accuracy and robustness. For these simulated scenes, 93% of the mixed pixels were restored to the surface to which they belong. This mixed pixel restoration process is shown to be accurate and robust for both simulated and real world scenes, thus provides a reliable alternative to removing mixed pixels that can be easily adapted to any mixed pixel detection algorithm.
Keywords :
image resolution; image restoration; image sensors; object detection; optical radar; amplitude modulated full-field range-imagers; full-field amplitude modulated continuous wave lidar systems; full-field range-imaging cameras; mixed pixel detection algorithm; mixed pixel restoration; surface projection; Amplitude modulation; Cameras; Clouds; Image restoration; Layout; Optical modulation; Pixel; Robustness; Signal processing; Surface fitting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Vision Computing New Zealand, 2009. IVCNZ '09. 24th International Conference
Conference_Location :
Wellington
ISSN :
2151-2205
Print_ISBN :
978-1-4244-4697-1
Electronic_ISBN :
2151-2205
Type :
conf
DOI :
10.1109/IVCNZ.2009.5378366
Filename :
5378366
Link To Document :
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