function y = noise(varargin)%  NOISE    Adds noise to an image.%%     NOISE creates a new image by adding noise to the original image.%     NOISE can be used to any matrix (1D, 2D, 3D, nD)%%     Noisetypes are:%       'ag' : additive gaussian (default)    'au' : additive uniform%       'mg' : multiplicative gaussian        'mu' : multiplicative uniform%       'sp' : salt and pepper%%     Additive noise sums an random value to the image value at each pixel,%     Multiplicative noise replaces a pixel value with an random value,%     Salt and Pepper noise replaces a pixel value with the maximum or minimum possible values.%%     For 'ag' noisetype use:  y = NOISE(x,'ag', variance, [incidence])%       where 'variance' is the variance of the gaussian noise added and the optional parameter%       'incidence' is the percetual of pixels affected be the noise (default for additive noise=1).%       For a 50% incidence use 'incidence' = .5 and so on.%%     For 'au' noisetype use :  y = NOISE(x,'au', maximum, [incidence])%       where 'maximum' is the maximum value the uniform noise can achieve%%     For 'mg' noisetype use :  y = NOISE(x,'mg', incidence)%     For 'mu' noisetype use :  y = NOISE(x,'mu', incidence)%       Multiplicative noisetypes require that the 'incidence' parameter. For this kind of noise%       the variance or the maximum (respectivelly for gaussian and uniform noisetypes) are allways%       set to the maximum image value.%%     For 'sp' noisetype use :  y = NOISE(x,'sp', incidence)%%     The 'maximum' and 'variance' parameters can be set as percentual of the maximum - minimum image %     values by using these values as strings containg the percentual rate followed by the percent symbol.%     The 'incidence' can also be expressed as a pecentual in this same way%%     Example:  y = NOISE(x,'ag', '25%')%               y = NOISE(x,'mu', 10, .5) -> same as y = NOISE(x,'mu',10, '50%')%[u, noisetype,  scale, incid] = parse_inputs(varargin{:});if ~isa(u,'double')   u = double(u);endy = u;n = zeros(size(u));if incid == 1   m_incid = logical(ones(size(u)));else   m_incid = rand(size(u));   m_incid = find(m_incid <= incid);endif strcmp(noisetype, 'ag')   n(m_incid) = scale*randn(size(m_incid));   y = u + n;   elseif strcmp(noisetype, 'au')   n(m_incid) = scale*rand(size(m_incid));   y = u + n;   elseif strcmp(noisetype, 'mg')   n(m_incid) = scale*randn(size(m_incid));   y(m_incid) = n(m_incid);   elseif strcmp(noisetype, 'mu')   n(m_incid) = scale*rand(size(m_incid));   y(m_incid) = n(m_incid);   elseif strcmp(noisetype, 'sp')   n(m_incid) = sign(randn(size(m_incid)));   umax = max(u(:));   umin = min(u(:));   salt = find(n==-1);   pepper = find(n==1);   y(salt) = umax;   y(pepper) = umin;endfunction [u, noisetype, scale, incid] = parse_inputs(varargin)switch nargincase 0   error('Too few inputs')   case 1   u = varargin{1};   noisetype = 'ag';   scale = double(max(u(:)));   incid = 1;   case 2   u = varargin{1};   if strmatch(varargin{2},['ag';'au'])      noisetype = varargin{2};      scale = double(max(u(:)));      incid = 1;   elseif strmatch(varargin{2},['mg'; 'mu'; 'sp'])      error('Incidence missing');   else      noisetype = 'ag';      scale = varargin{2};      incid = 1;   end   case 3   u = varargin{1};   if strmatch(varargin{2},['ag';'au'])      noisetype = varargin{2};      scale = varargin{3};      incid = 1;   elseif strmatch(varargin{2},['mg'; 'mu'; 'sp'])      noisetype = varargin{2};      scale = double(max(u(:)));      incid = varargin{3};   else      noisetype = 'ag';      scale = varargin{2};      incid = varargin{3};   end   case 4   u = varargin{1};   if strmatch(varargin{2},['ag';'au'])      noisetype = varargin{2};      scale = varargin{3};      incid = varargin{4};   else      error('Too many parameters')   end   otherwise   error('Too many parameters')endif findstr(scale,'%')   scale = ( double(max(u(:))) - double(min(u(:))) )*str2num(scale(1:end-1))/100;endif findstr(incid,'%')   incid = str2num(incid(1:end-1))/100;end