Fundamentals of digital image processing
Fundamentals of digital image processing
A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Multirate systems and filter banks
Multirate systems and filter banks
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Spatially adaptive wavelet thresholding with context modeling for image denoising
IEEE Transactions on Image Processing
MMSE Filtering of generalised signal-dependent noise in spatial and shift-invariant wavelet domains
Signal Processing - Special section: Advances in signal processing-assisted cross-layer designs
Filtering in Generalized Signal-Dependent Noise Model Using Covariance Information
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Nonlocal means-based speckle filtering for ultrasound images
IEEE Transactions on Image Processing
Engineering Applications of Artificial Intelligence
Derivation of centralized and distributed filters using covariance information
Computational Statistics & Data Analysis
Multiplicative Noise Removal with Spatially Varying Regularization Parameters
SIAM Journal on Imaging Sciences
Real time ultrasound image denoising
Journal of Real-Time Image Processing
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An original method to denoise ultrasonic images affected by speckle is presented. Speckle is modeled as a signal-dependent noise corrupting the image. Noise reduction is approached as a Wiener-like filtering performed in a shift-invariant wavelet domain by means of an adaptive rescaling of the coefficients of an undecimated octave decomposition. The scaling factor of each coefficient is calculated from local statistics of the degraded image, the parameters of the noise model, and the wavelet filters. Experimental results demonstrate that excellent background smoothing as well as preservation of edge sharpness and fine details can be obtained.