Fundamentals of digital image processing
Fundamentals of digital image processing
Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
A Review of Nonlinear Diffusion Filtering
SCALE-SPACE '97 Proceedings of the First International Conference on Scale-Space Theory in Computer Vision
Non-Linear Gaussian Filters Performing Edge Preserving Diffusion
Mustererkennung 1995, 17. DAGM-Symposium
Visualization and Processing of Tensor Fields (Mathematics and Visualization)
Visualization and Processing of Tensor Fields (Mathematics and Visualization)
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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. Most past approaches for denoising ultrasound images essentially blur the image, and they do not handle attenuation. Our approach, on the contrary, does not blur the image and does handle attenuation. Our denoising approach is based on frequency compounding, in which images of the same object are acquired in different acoustic frequencies, and then compounded. Existing frequency compounding methods have been based on simple averaging, and have achieved only limited enhancement. The reason is that the statistical and physical characteristics of the signal and noise vary with depth, and the noise is correlated. Hence, we suggest a spatially varying frequency compounding, based on understanding of these characteristics. Our method suppresses the various noise sources and recovers attenuated objects, while maintaining high resolution.