An image driven bilateral filter with adaptive range and spatial parameters for denoising Magnetic Resonance Images

Abstract Bilateral filter is an edge preserving denoising filter, widely used in medical image processing and raster graphics editors. Its performance greatly depends upon selection of spatial and radiometric parameters. Subjective selection of these parameters through trial and error can be sub-optimal. In this paper, an image driven method to compute the optimum values of spatial and radiometric parameters is proposed. Local optima of the parameters are adaptively estimated from the local grey level dispersion. The proposed method exhibited a Noise Suppression Ratio (NSR), Edge preservation Index (EPI) and Edge Strength Similarity Index Metric (ESSIM) of 0.62 ± 0.15, 0.76 ± 0.04 and 0.9998 ± 0.00005, respectively. It is superior to the method of computing the operational parameters from the standard deviation of noise in which the values of the performance matrices are NSR = 0.556 ± 0.223, EPI = 0.72 ± 0.01 and ESSIM = 0.9998 ± 0.0001. The bilateral filter with locally adaptive spatial and radiometric parameters could selectively denoise homogeneous regions, without degrading the morphological edges.

[1]  Jay Prakash,et al.  NSABC: Non-dominated sorting based multi-objective artificial bee colony algorithm and its application in data clustering , 2016, Neurocomputing.

[2]  Sanjay Ghosh,et al.  On Fast Bilateral Filtering Using Fourier Kernels , 2016, IEEE Signal Processing Letters.

[3]  Nagashettappa Biradar,et al.  Echocardiographic image denoising using extreme total variation bilateral filter , 2016 .

[4]  Yu Zhu,et al.  A sparse probabilistic approach with chaotic artificial bee colony optimization for sea clutter soft computing , 2016, Appl. Soft Comput..

[5]  Saime Akdemir Akar,et al.  Determination of optimal parameters for bilateral filter in brain MR image denoising , 2016, Appl. Soft Comput..

[6]  Ghassan Hamarneh,et al.  Bilateral Filtering of Diffusion Tensor Magnetic Resonance Images , 2007, IEEE Transactions on Image Processing.

[7]  Giuseppe Papari,et al.  Fast Bilateral Filtering for Denoising Large 3D Images , 2017, IEEE Transactions on Image Processing.

[8]  April Khademi,et al.  Image Enhancement and Noise Suppression for FLAIR MRIs With White Matter Lesions , 2010, IEEE Signal Processing Letters.

[9]  Byeong-Seok Shin,et al.  A fast 3D adaptive bilateral filter for ultrasound volume visualization , 2016, Comput. Methods Programs Biomed..

[10]  Shu-Tao Xia,et al.  Entropy-based bilateral filtering with a new range kernel , 2017, Signal Process..

[11]  Hans Knutsson,et al.  Bilateral Filtering of fMRI Data , 2008, IEEE Journal of Selected Topics in Signal Processing.

[12]  Kunal N. Chaudhury,et al.  Fast and Provably Accurate Bilateral Filtering , 2016, IEEE Transactions on Image Processing.

[13]  Ming Zhang,et al.  Multiresolution Bilateral Filtering for Image Denoising , 2008, IEEE Transactions on Image Processing.

[14]  Ye Chen,et al.  Optimization of Bilateral Filter Parameters via Chi-Square Unbiased Risk Estimate , 2014, IEEE Signal Processing Letters.

[15]  Thomas Beyer,et al.  MR–Consistent Simultaneous Reconstruction of Attenuation and Activity for Non–TOF PET/MR , 2016, IEEE Transactions on Nuclear Science.

[16]  Rynson W. H. Lau,et al.  Fast Weighted Histograms for Bilateral Filtering and Nearest Neighbor Searching , 2016, IEEE Transactions on Circuits and Systems for Video Technology.

[17]  Xiaopeng Zhang,et al.  Speeding Up the Bilateral Filter: A Joint Acceleration Way , 2016, IEEE Transactions on Image Processing.

[18]  Chandra Sekhar Seelamantula,et al.  Sure-fast bilateral filters , 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[19]  Jeny Rajan,et al.  Enhancement and bias removal of optical coherence tomography images: An iterative approach with adaptive bilateral filtering , 2016, Comput. Biol. Medicine.

[20]  Patrick Siarry,et al.  A sensitivity analysis method for driving the Artificial Bee Colony algorithm's search process , 2016, Appl. Soft Comput..

[21]  K. M. Mohsin,et al.  Bilateral filtering with adaptation to phase coherence and noise , 2013, Signal Image Video Process..

[22]  Isin Erer,et al.  Bilateral Filtering-Based Enhanced Pansharpening of Multispectral Satellite Images , 2014, IEEE Geoscience and Remote Sensing Letters.

[23]  Peng Ren,et al.  An adaptive bilateral filter based framework for image denoising , 2014, Neurocomputing.