  An efficient despeckling method using a quantum-inspired adaptive threshold
function is presented for reducing noise of ultrasound images. In the first
step, the ultrasound image is decorrelated by an spectrum equalization
procedure due to the fact that speckle noise is neither Gaussian nor white. In
fact, a linear filter is exploited to flatten the power spectral density (PSD)
of the ultrasound image. Then, the proposed method shrinks complex wavelet
coefficients based on the quantum-inspired adaptive threshold function. The
proposed approach has been used to denoise both real and simulated data sets
and compare with other widely adopted techniques. Experimental results
demonstrate that the proposed method has a competitive performance to remove
speckle noise and can preserve details and textures of medical ultrasound
images.
