Image Noise Reduction in Discrete Cosine Transform domain

Image noise reduction in the frequency domain by thresholding is simple, but quite effective. Wavelet domain thresholding has been an active area of research but relatively little work has been published on DCT domain denoising. A novel method for determining the hard threshold for the DCT domain denoising is proposed. The low amplitude DCT coefficients are discarded until the cumulative sum of the discarded signal energy is comparable to that of noise in each DCT block. Cycle spinning is also applied to reduce block artifacts. The proposed method is quite effective and simple enough to be used in portable devices.

[1]  I. Johnstone,et al.  Adapting to Unknown Smoothness via Wavelet Shrinkage , 1995 .

[2]  Jongho Kim.  Adaptive blocking artifact reduction using wavelet-based block analysis , 2009, IEEE Transactions on Consumer Electronics.

[3]  R. Eslami,et al.  The contourlet transform for image denoising using cycle spinning , 2003, The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003.

[4]  Wenjun Zhang,et al.  Adaptive reduction of blocking artifacts in DCT domain for highly compressed images , 2004, IEEE Trans. Consumer Electron..

[5]  Ji-Sang Yoo,et al.  A Face Tracking Algorithm for Multi-view Display System , 2013 .

[6]  Jechang Jeong,et al.  Adaptive deblocking method using a transform table of different dimension DCT , 2008, IEEE Transactions on Consumer Electronics.

[7]  Alessandro Foi,et al.  Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering , 2007, IEEE Transactions on Image Processing.

[8]  Seong-Won Lee,et al.  Noise-adaptive spatio-temporal filter for real-time noise removal in low light level images , 2005, IEEE Trans. Consumer Electron..

[9]  I. Johnstone,et al.  Ideal spatial adaptation by wavelet shrinkage , 1994 .

[10]  Martin Vetterli,et al.  Spatially adaptive wavelet thresholding with context modeling for image denoising , 2000, IEEE Trans. Image Process..

[11]  Sangkeun Lee,et al.  Edge statistics-based image scale ratio and noise strength estimation in DCT-coded images , 2009, IEEE Transactions on Consumer Electronics.

[12]  Max Mignotte,et al.  Fusion of regularization terms for image restoration , 2010, J. Electronic Imaging.

[13]  Roberto Manduchi,et al.  Bilateral filtering for gray and color images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[14]  Seungjoon Yang,et al.  Block-based noise estimation using adaptive Gaussian filtering , 2005, 2005 Digest of Technical Papers. International Conference on Consumer Electronics, 2005. ICCE..

[15]  Giuseppe Messina,et al.  Fast method for noise level estimation and integrated noise reduction , 2005, IEEE Transactions on Consumer Electronics.

[16]  Karen O. Egiazarian,et al.  Shape-adaptive DCT for denoising and image reconstruction , 2006, Electronic Imaging.

[17]  C.-C. Jay Kuo,et al.  Improved image denoising with adaptive nonlocal means (ANL-means) algorithm , 2010, IEEE Transactions on Consumer Electronics.