Robust spline smoothing for 1-D to N-D data 1.0

SMOOTHN provides a fast, unsupervised and robust discretized spline smoother for data of any dimension.SMOOTHN(Y) automatically smoothes the uniformly-sampled array Y. Y can be any N-D noisy array (time series, images, 3D data,...).SMOOTHN can deal with missing (NaN) values (see screenshot, top panels).SMOOTHN(...,'robust') carries out a robust smoothing that minimizes the influence of outlying data (see screenshot, bottom right panel).SMOOTHN is made automated by the minimization of the generalized cross-validation score.Enter "help smoothn" in the Matlab command window for complete instructions and 1-D to 3-D examples.------Here is an example that requires the Image Processing Toolbox. The example below applies SMOOTHN to an image of Saturn that has had Gaussian noise added. Read the "Saturn" image from MatlabI = rgb2gray(imread('saturn.png')); Add Gaussian noise to the imageJ = imnoise(I,'gaussian',0,0.025); Remove the noise using the SMOOTHN function. Let SMOOTHN choose the amount of smoothness automaticallyK = smoothn(J);K = uint8(K); % back to 8-bit integer format Now check the resultsubplot(121), imshow(J), title('Noisy Saturn')subplot(122), imshow(K), title('Denoised Saturn')------Other 1-D to 3-D examples are given in:http://www.biomecardio.com/matlab/smoothn.html-----For details about the algorithm, refer to:http://www.biomecardio.com/pageshtm/publi/csda10.pdf

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	Added,  Amount,  Applies,  Choose,  Function,  Gaussian,  Image,  Imagej,  Imnoisei Gaussian,  Matlabi,  Noise,  Processing,  Quotsaturnquot,  Remove,  Rgb Grayimread Saturnpng,  Saturn,  Smoothness,  Toolbox
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