Abstract
The key of wavelet image threshold de-noising is the choice of the threshold function and the threshold value. To overcome the shortcomings of constant deviation existing between estimated wavelet coefficients and decomposition coefficients in the soft threshold function and discontinuity of the hard threshold function, a new threshold function based on wavelet shrinkage in image de-noising is presented in this paper. Threshold values of images with different edges and texture degrees are fine-tuned when the threshold value is set. Furthermore, a self-adaption optimal threshold which is fit to all scale levels is designed based on features of multiscale and multiresolution of wavelet transform. Simulation results show that the proposed methods are efficient to reduce the noise while preserving the detail information of the image.
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