DocumentCode
518998
Title
Notice of Retraction
Research on the edge detection algorithm of vehicles based on the dyadic wavelet
Author
Xiaoping Li ; Shuaizong Wang ; Yinxiang Li ; Jianqiang Xu
Author_Institution
Dept. of Comput. Sci. & Technol., Beijing Inst. of Technol., Beijing, China
fYear
2010
fDate
11-13 May 2010
Firstpage
337
Lastpage
340
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
The advantage of wavelet technology can separate the signal and the noise, thereby enhancing the output the ratio of signal to noise. In the outdoor environment, under the high noise, it proposes one algorithm based on dyadic wavelet to process the signals and noises in images of vehicles through the wavelet transform at different scales and different characteristics, which can adjust its threshold automatically. Experiment shows that this method is feasible, fast and adaptive filtering.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
The advantage of wavelet technology can separate the signal and the noise, thereby enhancing the output the ratio of signal to noise. In the outdoor environment, under the high noise, it proposes one algorithm based on dyadic wavelet to process the signals and noises in images of vehicles through the wavelet transform at different scales and different characteristics, which can adjust its threshold automatically. Experiment shows that this method is feasible, fast and adaptive filtering.
Keywords
edge detection; filtering theory; image denoising; wavelet transforms; adaptive filtering; dyadic wavelet technology; edge detection algorithm; wavelet transform; Continuous wavelet transforms; Discrete wavelet transforms; Filtering; Image edge detection; Image processing; Signal processing; Vehicle detection; Vehicles; Wavelet transforms; Working environment noise; dyadic wavelet; edge detection; wavelet;
fLanguage
English
Publisher
ieee
Conference_Titel
New Trends in Information Science and Service Science (NISS), 2010 4th International Conference on
Conference_Location
Gyeongju
Print_ISBN
978-1-4244-6982-6
Type
conf
Filename
5488595
Link To Document