A Novel Adaptive Underwater Image Biorthogonal Basic Wavelet Transform De-Noising Approach

Abstract:

AUVs are usually equipped with video cameras to obtain the environment underwater information. Underwater images often suffer from effects such as diffusion, scatter and caustics. In order to improve the image quality and contrast, image restoration is need to be carried out before other image process. In this paper, a novel adaptive de-noising algorithm based on multi-wavelet transform was proposed in order to remove the Gaussian noise from the blurred underwater image. Firstly, the Gaussian noise deterioration of the image model was given. Secondly, the wavelet transform algorithm using Biorthogonal as a basic wavelet for underwater image decomposition and reconstruction was presented. Finally, Haar and Biorthogonal basic wavelet were chosen separately for adaptive de-noising algorithm for the blurred image restoration. By contrast with other filter methods, the experiment results verified its useful behaviors, and demonstrate that the raised de-noising approach can achieve fairly desired de-noising effectiveness for underwater image.

• Periodical: Applied Mechanics and Materials (Volumes 411-414)
• Pages: 1335-1340
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.411-414.1335
• Online since: September 2013
• Authors: Ming Wei Sheng, Yong Jie Pang, Hai Huang, Tie Dong Zhang
• Keywords: Adaptive De-Noising Algorithm, Biorthogonal Basic Wavelet Transform, De-Noising Approach, Underwater Image De-Noising

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