The Autonomous Underwater Vehicle Vision Denoising Method of Surfacelet Based on Sample Matrix

Authors:
Dan-Dan Liu
Affiliations:
Heilongjiang Institute of Science and Technology, Harbin, P.R. China 150027
Venue:
ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part I
Year:
2008

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Abstract

Through analyzing needs of the autonomous underwater vehicle vision, the autonomous underwater vehicle vision denosing method of Surfacelet based on sample matrix is proposed. N nosing image are produced by one image adding noise based on N sample matrix, which are circle shifted respectively and constructed image sequence. The image sequence is implemented Surfacelet transform and employed the hard thresholding denoising to coefficient and then linear average in airspace. The experimental results indicate that image de-noised has not Gibbs--like phenomena of Wavelet and nick effect. The method can restrain noise to underwater sonar image and hold detail and texture of image to target fringe of noise distribute strongly. The method has important significance to autonomous underwater vehicle planning for safe navigation routes and successful completion of the tasks.