Quantum-Inspired Weighted Bilateral Filtering for Despeckling in Ultrasound Images

Abstract

The ultrasound is a nondestructive technique used widely in the medical field for detection of soft tissues in the human body. But this should be validated by an expert radiologist, since ultrasound images are highly affected by noises. In this paper four methods for denoising the speckle noise are compared and analyzed, namely, diffusion tensors, heavy-tailed Levy's distribution, quantum inspired bilateral filtering and locally adaptive wavelet domain Bayesian processor. Performances of each method were quantified by means of Peak Signal to Noise Ratio (PSNR) and Mean Structural Similarity Index Matrix (MSSIM). It was found that denoising of US images through QWBF has higher PSNR value of 16.75 and MSSIM of 0.88. Hence this method was proved to be more efficient compared to other three methods presented in this paper.