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Ultrasound images are very noisy. Along with system noise, a significant noise source is the speckle phenomenon caused by interference in the viewed object. The noise of ultrasound image was always deemed as multiplicative noise, but the present multiplicative noise models are not fitting for it very well, because the noise is more complex than the simple multiplicative one. So we should consider...
Image diffusion on implicit surfaces is solved by the concepts of intrinsic gradient and intrinsic divergence along with the expression of implicit surfaces using zero level set of a continuous signed distance function. But the finite difference scheme of the relevant gradient descent equations is complex and its computation efficiency is low. The Split Bregman algorithm for the nonlinear variational...
The TV-L1 model for image diffusion can preserve geometry and reduce the loss of image contrast better than the classical TV-L2 model, but its traditional difference scheme is complex and its computation efficiency is low. The minimization of energy functional of the TV-LI model is transformed to three simple sub-problems by means of introducing two auxiliary variables to reduce complexity, and its...
Images can be decomposed into structural component and textural component with the variational OSV (Osher-Sole-Vese) model for image decomposition, but the minimization problem must be realized through solving some 4th order partial differential equations (PDE) by means of complex finite difference scheme for Laplacian of curvature which leads to low computational efficiency. The Split Bregman method...
Ultrasound images are very noisy. Along with system noise, a significant noise source is the speckle phenomenon, caused by interference in the viewed object. The noise of ultrasound image was always deemed as multiplicative noise. But the multiplicative noise models are not fitting for it very well, because the noise is more complex than the simple multiplicative one. In ultrasound image, the perfect...
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