Denoising and enhancement in intravascular ultrasound images via multiscale analysis
Hui Wang · Journal of Sichuan University · 2008
An algorithm based on dyadic wavelet transform for speckle reduction and contrast enhancement in intravascular ultrasound images was presented. Wavelet shrinkage techniques which combined soft and hard thresholding were applied to coefficients of logarithmically transformed images since scattering from red blood cells (blood speckle noise) was multiplicative noise and a method to estimate local threshold was proposed. In addition, a fast contrast enhancement algorithm based on multi-scale edges representation of images through stretching the local extrema and interpolating them with Hermite interpolation polynomials was carried out. Experiments with clinical images showed that this algorithm was capable of not only reducing the speckle noise of blood but also enhancing features of diagnostic importance of intravascular ultrasound images and produced superior results qualitatively when compared to results obtained from existing denoising methods alone.