Speckle Noise Reduction and Edge Enhancement in Ultrasound Images Based on Wavelet Transform
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초록
For B-mode ultrasound images, we propose an image enhancement algorithm based on a multi-resolution approach, which consists of edge enhancing and noise reducing procedures. Edge enhancement processing is applied sequentially to coarse-to-fine resolution images obtained from wavelet-transformed data. In each resolution, the structural features of each pixel are examined through eigen analysis. Then, if a pixel belongs to an edge region, we perform two-step filtering: that is, directional smoothing is conducted along the tangential direction of the edge to improve continuity and directional sharpening is conducted along the normal direction to enhance the contrast. In addition, speckle noise is alleviated by proper attenuation of the wavelet coefficients of the homogeneous regions at each band. This region-based speckle-reduction scheme is differentiated from other methods that are based on the magnitude statistics of the wavelet coefficients. The proposed algorithm enhances edges regardless of changes in the resolution of an image, and the algorithm efficiently reduces speckle noise without affecting the sharpness of the edge. Hence, compared with existing algorithms, the proposed algorithm considerably improves the subjective image quality without providing any noticeable artifacts.
Abstract
For B-mode ultrasound images, we propose an image enhancement algorithm based on a multi-resolution approach, which consists of edge enhancing and noise reducing procedures. Edge enhancement processing is applied sequentially to coarse-to-fine resolution images obtained from wavelet-transformed data. In each resolution, the structural features of each pixel are examined through eigen analysis. Then, if a pixel belongs to an edge region, we perform two-step filtering: that is, directional smoothing is conducted along the tangential direction of the edge to improve continuity and directional sharpening is conducted along the normal direction to enhance the contrast. In addition, speckle noise is alleviated by proper attenuation of the wavelet coefficients of the homogeneous regions at each band. This region-based speckle-reduction scheme is differentiated from other methods that are based on the magnitude statistics of the wavelet coefficients. The proposed algorithm enhances edges regardless of changes in the resolution of an image, and the algorithm efficiently reduces speckle noise without affecting the sharpness of the edge. Hence, compared with existing algorithms, the proposed algorithm considerably improves the subjective image quality without providing any noticeable artifacts.
참고문헌 (20)
- Macovski, "Medical Imaging Systems" (1983), Prentice-Hall
- J.U.Quistgaard, "Signal acquisition and processing in medical diagnostic ultrasound", IEEE Signal Processing Magazine, 14, pp.67~74 (1997)
- P.N.T.Wells, "Ultrasonic imaging of the human body", Reports on Progress in Physics, 62, pp.671~722 (1995)
- A. K. Jain, "Fundamentals of Digital Image Processing" (1989), Englewood Cliffs, NJ: Prentice-Hall
- T. Loupas, "An adaptive weighted median filter for speckle suppression in medical ultrasonic images", IEEE Trans. Circuits Syst, 36, pp.129~135 (1989)
- J. C. Bamber, "Adaptive filtering for reduction of speckle in ultrasonic pulse-echo images", Ultrasonics, pp.41~44 (1986)
- J. Weickert, "Multiscale texture enhancement", in Computer Analysis of Images and Patterns; Lecture Notes in Computer Science, 970, pp.230~237 (1995)
- K. Z. Abd-Elmoniem, "Real-time speckle reduction and coherence enhancement in ultrasound imaging via nonlinear anisotropic diffusion", IEEE Trans. Biomedical Engineering, 49(9), pp.997~1014 (2002)
- M. M. Goodsitt, "Real-time B-mode ultrasound quality control test procedures: Report of AAPM ultrasound task group no. 1", Med. Phys, 25(8), pp.1385~1406 (1998)
- N. M. Gibson, "A computerized quality control testing system for B-mode ultrasound", Ultrasound in Med. & Biol, 27(12), pp.1697~1711 (2001)
- R. M. Rao, "Wavelet Transforms: Introdu- ction to Theory and Applications" (1998), Addison Wesley Publications
- D. L. Donoho, "De-noising by soft-thresholding", IEEE Trans. Information theory, 41(3), pp.613~627 (1995)
- X. Zong, "Speckle reduction and contrast enhancement of echocardiogram via multiscale Nonlinear Processing", IEEE Trans. Med. Imag, 17 (1998)
- Q. Zhou, "Denoise and contrast enhancement of ultrasound speckle image based on wavelet", in Proc. International Conference on Signal Processing., pp.1500~1503 (2002)
- A. Achim, "Novel Bayesian multiscale method for speckle removal in medical ultrasound images", IEEE Trans. Med. Imag, 20(8), pp.772~783 (2001)
- X. Hao, "A novel multiscale nonlinear thresholding method for ultrasonic speckle suppressing", IEEE Trans. Med. Imag, 18(9), pp.787~794 (1999)
- A. Laine, "Wavelets for contrast enhan- cement of digital mammography", IEEE Eng. Med. Biol, pp.536~550 (1995)
- P. Sakellaropoulos, "A wavelet-based spatially adaptive method for mammographic contrast enhancement", Phys. Med. Biol, 48, pp.787~803 (2003)
- Y. Xu, "Wavelet transform domain filters: a spatially selective noise filtration technique", IEEE Trans. Image Processing, 3(6), pp.747~758 (1994)
- W H. Press, "Numerical recipes in C - The art of scientific computing", pp.463~469, Cambridge University press
