Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Segmentation of ultrasound liver images: an automatic approach
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Entropy-based algorithms for best basis selection
IEEE Transactions on Information Theory - Part 2
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Finding out general tendencies in speckle noise reduction in ultrasound images
Expert Systems with Applications: An International Journal
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This paper presents the comparative study of various wavelet filter based denoising methods according to different thresholding values applied to ultrasound images. An original image is transformed into a multi scale wavelet domain and the wavelet coefficients are processed by a soft thresholding method. The denoised image is the output image obtained from the inverse wavelet transform of the threshold coefficients using Donoho's method. It has been observed that such denoising methods are effective in the sense that they preserve the edge details besides suppressing the noise. The comparative evaluation of the denoising performance is shown using statistical significance tests for different wavelet filters. Image quality parameters such as peak signal-to-noise ratio, normalized mean square error, and correlation coefficient have been used to evaluate the performance of wavelet filters. The performance has also been compared with the adaptive weighted median filtering method.