Ultrasound Speckle Reduction in the Complex Wavelet Domain

Ultrasound Speckle Reduction in the Complex Wavelet Domain

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Ultrasound is a non-invasive, portable, and low cost imaging modality that offers real-time image formation and has many applications in medicine. Unfortunately, ultrasound images are inherently degraded by a multiplicative noise called speckle that makes further analysis difficult. As a result, a vast number of ultrasound despeckling methods have been introduced. One of the most successful multiscale Bayesian techniques is based on modeling the wavelet coefficients of the logarithmically transformed ultrasound images using a SαS prior. These improvements can be explained by two special characteristics of DTCWT; DTCWT is approximately shift invariant and it has better directional selectivity compared to standard wavelet transforms. Therefore, the DTCWT is proposed as a good candidate for ultrasound despeckling.

Inspec keywords: Bayes methods; wavelet transforms; ultrasonic imaging; speckle; image denoising; medical image processing; real-time systems

Other keywords: shift invariant approximation; ultrasound despeckling methods; ultrasound speckle reduction; complex wavelet domain; multiscale Bayesian techniques; wavelet coefficients; low cost imaging modality; multiplicative noise; DTCWT; logarithmic ultrasound images transformation; real-time image formation; SαS prior

Subjects: Optical, image and video signal processing; Integral transforms; Probability theory, stochastic processes, and statistics; Integral transforms; Sonic and ultrasonic applications; Medical and biomedical uses of fields, radiations, and radioactivity; health physics; Computer vision and image processing techniques; Biology and medical computing; Other topics in statistics

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