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An Adaptive Threshold Method for WMSN Image Denoising

Received: 2 January 2020 Accepted: 20 March 2020 Though the wavelet threshold algorithm has been demonstrated to be a very effective tool to denoise the images with low levels of noise, it usually losses the power to well preserve meaningful details in images. To this end, this paper proposed an adaptive threshold denoising method for images that are usually interfered by noise on the Wireless Multimedia Sensor Network (WMSN). First, a scale parameter equation was defined according to different sub-band characteristics after the images were subject to wavelet decomposition, so as to determine the adaptive optimal threshold suitable for each scale level; Second, a new derivable threshold function was designed in this paper; Third, after comparison, proper wavelet basis function was selected for image denoising accordingly. Moreover, the test results on several test images proved the superiority of the proposed method over some classical methods in terms of PSNR and MSE.