Research on image denoising methods based on wavelet transform and rolling-ball algorithm

A novel image de-noising method based on rolling-ball algorithm is proposed. And wavelet transform is applied to do with strong noising image. Firstly, the image is denoised by wavelet transform in frequency domain. Then, the image is denoised by rolling-ball algorithm in space domain. The validity of the proposed approach is demonstrated in the real flame images polluted seriously by the noise. Experiment results show good denoising effect and the proposed approach could be applied in other industrial images.

[1]  Mostafa Kaveh,et al.  Fourth-order partial differential equations for noise removal , 2000, IEEE Trans. Image Process..

[2]  John W. Tukey,et al.  Exploratory Data Analysis. , 1979 .

[3]  Pak-Chung Ching,et al.  On wavelet denoising and its applications to time delay estimation , 1999, IEEE Trans. Signal Process..

[4]  John G. Harris,et al.  Wavelet denoising of chirp-like signals in the Fourier domain , 1999, ISCAS'99. Proceedings of the 1999 IEEE International Symposium on Circuits and Systems VLSI (Cat. No.99CH36349).

[5]  Tai-Chiu Hsung,et al.  Image denoising using wavelet transform modulus sum , 1998, ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344).

[6]  B I Justusson,et al.  Median Filtering: Statistical Properties , 1981 .

[7]  Laurent D. Cohen,et al.  On active contour models and balloons , 1991, CVGIP Image Underst..

[8]  Donald Geman,et al.  Constrained Restoration and the Recovery of Discontinuities , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  J. Sethian,et al.  Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations , 1988 .

[10]  David Dagan Feng,et al.  Embedded singularity detection zerotree wavelet coding , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[11]  Ioannis Pitas,et al.  Nonlinear Digital Filters - Principles and Applications , 1990, The Springer International Series in Engineering and Computer Science.

[12]  B Liu,et al.  Spectrogram enhancement algorithm: a soft thresholding-based approach. , 1999, Ultrasound in medicine & biology.

[13]  V. Ralph Algazi,et al.  Image enhancement using linear diffusion and an improved gradient map estimate , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[14]  J. Astola,et al.  Fundamentals of Nonlinear Digital Filtering , 1997 .

[15]  Dennis M. Healy,et al.  Wavelet transform domain filters: a spatially selective noise filtration technique , 1994, IEEE Trans. Image Process..

[16]  Thomas S. Huang,et al.  A generalization of median filtering using linear combinations of order statistics , 1983 .

[17]  Ken D. Sauer,et al.  A generalized Gaussian image model for edge-preserving MAP estimation , 1993, IEEE Trans. Image Process..

[18]  B. Vidakovic,et al.  On time-dependent wavelet denoising , 1998, IEEE Trans. Signal Process..

[19]  S. Krishnan,et al.  Denoising knee joint vibration signals using adaptive time-frequency representations , 1999, Engineering Solutions for the Next Millennium. 1999 IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.99TH8411).

[20]  Dadang Gunawan Denoising images using wavelet transform , 1999, 1999 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM 1999). Conference Proceedings (Cat. No.99CH36368).