log gabor 滤波器matlab程序

% gaborconvolve - function for convolving each row of an image with 1D % log-Gabor filters（利用一维盖伯滤波器对图像进行处理） % Usage: % [template, mask] = createiristemplate(eyeimage_filename) % Arguments: % im - the image to convolve % nscale - number of filters to use % minWaveLength - wavelength of the basis filter % mult - multiplicative factor between each filter % sigmaOnf - Ratio of the standard deviation of the Gaussian describing % the log Gabor filter's transfer function in the frequency % domain to the filter center frequency. % Output: % E0 - a 1D cell array of complex valued comvolution results function [EO, filtersum] = gaborconvolve(im, nscale, minWaveLength, mult, ... sigmaOnf) [rows cols] = size(im); %filtersum = zeros(1,size(im,2)); EO = cell(1, nscale); % Pre-allocate cell array ndata = cols; if mod(ndata,2) == 1 % If there is an odd No of data points ndata = ndata-1; % throw away the last one. end logGabor = zeros(1,ndata); result = zeros(rows,ndata); filtersum = logGabor; radius = [0:fix(ndata/2)]/fix(ndata/2)/2; % Frequency values 0 - 0.5 radius(1) = 1; wavelength = minWaveLength; % Initialize filter wavelength. for s = 1:nscale, % For each scale. % Construct the filter - first calculate the radial filter component. fo = 1.0/wavelength; % Centre frequency of filter. rfo = fo/0.5; % Normalised radius from centre of frequency plane % corresponding to fo. logGabor(1:ndata/2+1) = exp((-(log(radius/fo)).^2) / (2 * log(sigmaOnf)^2)); logGabor(1) = 0; filter = logGabor; filtersum = filtersum+filter; % for each row of the input image, do the convolution, back transform for r = 1:rows % For each row signal = im(r,1:ndata); imagefft = fft( signal ); result(r,:) = ifft(imagefft .* filter); end % save the ouput for each scale EO{s} = result; wavelength = wavelength * mult; % Finally calculate Wavelength of next filter end % ... and process the next scale filtersum = fftshift(filtersum);