Adaptive spatio-temporal filtering for video denoising using integer wavelet transform

In this paper, Spatial video denoising using wavelet transform has been focussed as it requires less computation and more suitable for real-time applications. Two specific techniques for spatial video denoising using wavelet transform are considered in this work, 2D Discrete Wavelet Transform (2D DWT) and Integer wavelet transform. Each of these techniques has its advantages and disadvantages. The first technique gives less quality at high levels of noise but consumes less time while the second gives high quality video while consuming long. In this work, we introduce an intelligent denoising system that makes a trade-off between the quality of the denoised video and the time required for denoising. The simulation results show that the proposed system is more suitable for real time applications where the time is critical while giving high quality videos especially at low to moderate levels of noise.

[1]  Ingrid Daubechies,et al.  Ten Lectures on Wavelets , 1992 .

[2]  S. Selvakumaran,et al.  A bivariate shrinkage function for complex dual tree DWT based image denoising , 2006 .

[3]  M. Bernas,et al.  Image quality evaluation , 2002, International Symposium on VIPromCom Video/Image Processing and Multimedia Communications.

[4]  Levent Sendur,et al.  A bivariate shrinkage function for wavelet-based denoising , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[5]  Levent Sendur,et al.  Bivariate shrinkage functions for wavelet-based denoising exploiting interscale dependency , 2002, IEEE Trans. Signal Process..

[6]  Ivan W. Selesnick,et al.  Video denoising using 2D and 3D dual-tree complex wavelet transforms , 2003, SPIE Optics + Photonics.

[7]  Yuan F. Zheng,et al.  Combined spatial and temporal domain wavelet shrinkage algorithm for video denoising , 2006, IEEE Transactions on Circuits and Systems for Video Technology.

[8]  Alin Achim,et al.  Image denoising using bivariate α-stable distributions in the complex wavelet domain , 2005, IEEE Signal Processing Letters.

[9]  Zoran Bojkovic,et al.  Image quality evaluation: JPEG 2000 versus intra-only H.264/AVC High Profile , 2007 .

[10]  Simon Haykin,et al.  Image Denoising by Sparse Code Shrinkage , 2001 .

[11]  Yuan F. Zheng,et al.  Feature-based wavelet shrinkage algorithm for image denoising , 2005, IEEE Transactions on Image Processing.

[12]  Amany M. Sarhan,et al.  Comparison between Discrete Wavelet Transform and Dual-Tree Complex wavelet Transform in Video Sequences Using Wavelet-Domain , 2008 .

[13]  Mohammed Ghazal,et al.  A Real-Time Technique for Spatio–Temporal Video Noise Estimation , 2007, IEEE Transactions on Circuits and Systems for Video Technology.

[14]  Chunyan Wang,et al.  FPGA Architecture for Real-Time Video Noise Estimation , 2006, 2006 International Conference on Image Processing.

[15]  J. M. Lilly,et al.  On the Design of Optimal Analytic Wavelets , 2008 .