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Ultrasound imaging is widely used for diagnostic purposes among the clinicians. A major problem concerning the ultrasound images is their inherent corruption by the multiplicative speckle noise that hampers the quality of the diagnosis, and reduces the efficiency of the algorithms for automatic image processing. In this paper, we propose a new spatially adaptive wavelet-based method in order to reduce...
A major problem concerning ultrasound images is their inherent corruption with speckle noise. Homomorphic wavelet-based methods using parametric models are widely used for despeckling ultrasound images. However, the efficiency of these methods greatly depends on the accuracy of the prior distribution used for modelling of the non-Gaussian statistics of the wavelet coefficients of the log-transformed...
A perceptual non-expansive image compression scheme using the nearly-orthogonal wavelets is presented in this paper. The proposed approach differs from the conventional design scheme by incorporating the human visual system characteristics directly in each sub-band of the wavelet decomposed image. The enhancement in the visual quality of the reconstructed image is achieved by using the proposed contrast...
A major problem in medical ultrasonography is the inherent corruption of ultrasound images with speckle noise that severely hampers the diagnosis and automatic image processing tasks. In this paper, an efficient wavelet-based method is proposed for despeckling medical ultrasound images. A closed-form Bayesian wavelet-based maximum a posteriori denoiser is developed in a homomorphic framework, based...
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