An Approach for Underwater Image Denoising Via Wavelet Decomposition and High-pass Filter

Wavelet-based denoising has comprehensive functionalities including feature extraction and low-pass filtering, while keeping characteristics such as low entropy, multi-resolution, irrelevance, etc. Wavelet-based denoising methods have been successfully applied for image processing in varieties. However, one of the main factors degrading underwater imaging is the backward scattered light, which performs as the color noise with significant low-frequency components. The current wavelet denoising methods are not optimal to depress such kind of strong co-related noise. Investigations have shown that the back-scattering noise is sensitive to high-pass filter. In this paper, we proposed a new approach for underwater image denoising by combining wavelet decomposition with high-pass filter. Thereby both the low-frequency components of the back-scattering noise and the uncorrelated high-frequency noise can be effectively depressed simultaneously. Experimental results were given.