This paper presents a wavelet-based hybrid threshold method according to the soft- and hard-threshold
functions proposed by Donoho. The wavelet-based hybrid threshold method may help doctors to know more details
on the liver disease through denoising the ultrasound image of the liver. First of all, an analytical expression for
the hybrid threshold function is discussed. The wavelet-based hybrid threshold method is then investigated for
ultrasound image of the liver. Finally, we test the influence of this parameter on the proposed method with the
real ultrasound image corrupted by speckle noise with different variances. Moreover, we compare the proposed
method under the varying parameters with the soft-threshold function and the hard-threshold function. Three
metrics, which are correlation coefficient, edge preservation index and structural similarity index, are measured
to quantify the denoised results of ultrasound liver image. Experimental results demonstrate the potential of the
proposed method for ultrasound liver image denosing.
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