from
Steerable Gaussian Filters
by Douglas Lanman
Evaluates the directional derivative of an image along an arbitrary axis.
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| runDemo.m |
% Clear Matlab command window.
clc;
% Example #1: Basic usage.
% Note: Filters are computed for each run.
disp('Example #1: Basic Usage');
theta = [0:15:360];
for i = [1:length(theta)]
[J,H] = steerGauss([],theta(i),3,true);
filters{i} = H;
pause(0.1);
end
disp(' Press any key to continue.'); pause;
% Load "mandrill" test image.
I = imread('mandrill.jpg');
% Example #2: Using pre-computed filters.
disp('Example #2: Using pre-computed filters.');
for i = [1:length(filters)]
[J,H] = steerGauss(I,filters{i},true);
pause(0.1);
end
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