Low-light imaging method with visible-band and wide-band image pair
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Noiseless codelength in wavelet denoising
EURASIP Journal on Advances in Signal Processing
Switching bilateral filter with a texture/noise detector for universal noise removal
IEEE Transactions on Image Processing
Chroma noise reduction in DCT domain using soft-thresholding
Journal on Image and Video Processing - Special issue on emerging methods for color image and video quality enhancement
An MMSE approach to nonlocal image denoising: Theory and practical implementation
Journal of Visual Communication and Image Representation
A multiresolution framework for local similarity based image denoising
Pattern Recognition
Pattern Recognition Letters
Journal of Visual Communication and Image Representation
Super-resolution texture synthesis using stochastic PAR/NL model
Journal of Visual Communication and Image Representation
Improved bilateral filter for suppressing mixed noise in color images
Digital Signal Processing
Adaptive non-local means filter for image deblocking
Image Communication
Image denoising using SVM classification in nonsubsampled contourlet transform domain
Information Sciences: an International Journal
De-noising of GPS Receivers Positioning Data Using Wavelet Transform and Bilateral Filtering
Wireless Personal Communications: An International Journal
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The bilateral filter is a nonlinear filter that does spatial averaging without smoothing edges; it has shown to be an effective image denoising technique. An important issue with the application of the bilateral filter is the selection of the filter parameters, which affect the results significantly. There are two main contributions of this paper. The first contribution is an empirical study of the optimal bilateral filter parameter selection in image denoising applications. The second contribution is an extension of the bilateral filter: multiresolution bilateral filter, where bilateral filtering is applied to the approximation (low-frequency) subbands of a signal decomposed using a wavelet filter bank. The multiresolution bilateral filter is combined with wavelet thresholding to form a new image denoising framework, which turns out to be very effective in eliminating noise in real noisy images. Experimental results with both simulated and real data are provided.