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
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