Spatially adaptive thresholding in wavelet domain for despeckling of ultrasound images

Systematic Evaluation on Speckle Suppression Methods in Examination of Ultrasound Breast Images

“…For the reason that the sparsity of wavelet coefficient, i.e., a few large coefficients contains most of information of the signal, the filtering processing can perform according to a threshold. After the idea of soft-thresholding de-noising first presented by Donoho [10], many researchers [33][34][35] tend to apply the WTF filter to de-speckling of the medical ultrasound image. Generally, WTF can be expressed as follows…”

Adaptive speckle reduction in ultrasound images using fuzzy logic on Coefficient of Variation

“…Thus, the designed weighted averaging filter changes the weights used adapting to the type of image and quantity of noise affecting the image. [11], (e) adaptive bilateral filter [12], (f) ATMAV [16], and (g) proposed adaptive fuzzy logic filter based on CV. 9.…”

“…Pizurica et al [10] proposed a generalised likelihood (GenLik) method in which wavelet coefficients are denoised by likelihood ratio using local neighbours following non-homomorphic filtering technique. An adaptive wavelet thresholding technique was proposed in [11] based on Bayesian maximum aposteriori probability (MAP) by modelling the noise free signal coefficients as symmetric normal inverse Gaussian and noisy coefficients as Gaussian distribution. From this, an adaptive threshold is obtained to reduce the speckle noise in ultrasound images.…”

An Optimal Control Algorithm Research of Biological Image Quality based on Quantum and Wavelet

“…We use the comparison methods such as Mean, Wiener [10] , TV [13] , soft and hard threshold [9] . From Table 1, the value of PSNR is bigger than other algorithms under the same  .…”