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In many applications, Image de-noising and improvement represent essentialprocesses in presence of colored noise such that in underwater. Power spectraldensity of the noise is changeable within a definite frequency range, andautocorrelation noise function is does not like delta function. So, noise inunderwater is characterized as colored noise. In this paper, a novel imagede-noising method is proposed using multi-level noise power estimation indiscrete wavelet transform with different basis functions. Peak signal to noiseratio (PSNR) and mean squared error represented performance measures that theresults of this study depend on it. The results of various bases of waveletsuch as: Daubechies (db), biorthogonal (bior.) and symlet (sym.), show thatdenoising process that uses in this method produces extra prominent images andimproved values of PSNR than other methods.

Image denosing in underwater acoustic noise using discrete wavelet transform with different noise level estimation