www.pudn.com > iriscode.zip > nonmaxsup.m
% NONMAXSUP
%
% Usage:
% im = nonmaxsup(inimage, orient, radius);
%
% Function for performing non-maxima suppression on an image using an
% orientation image. It is assumed that the orientation image gives
% feature normal orientation angles in degrees (0-180).
%
% input:
% inimage - image to be non-maxima suppressed.
%
% orient - image containing feature normal orientation angles in degrees
% (0-180), angles positive anti-clockwise.
%
% radius - distance in pixel units to be looked at on each side of each
% pixel when determining whether it is a local maxima or not.
% (Suggested value about 1.2 - 1.5)
%
% Note: This function is slow (1 - 2 mins to process a 256x256 image). It uses
% bilinear interpolation to estimate intensity values at ideal, real-valued pixel
% locations on each side of pixels to determine if they are local maxima.
%
% Peter Kovesi pk@cs.uwa.edu.au
% Department of Computer Science
% The University of Western Australia
%
% December 1996
function im = nonmaxsup(inimage, orient, radius)
if size(inimage) ~= size(orient)
error('image and orientation image are of different sizes');
end
if radius < 1
error('radius must be >= 1');
end
[rows,cols] = size(inimage);
im = zeros(rows,cols); % Preallocate memory for output image for speed
iradius = ceil(radius);
% Precalculate x and y offsets relative to centre pixel for each orientation angle
angle = [0:180].*pi/180; % Array of angles in 1 degree increments (but in radians).
xoff = radius*cos(angle); % x and y offset of points at specified radius and angle
yoff = radius*sin(angle); % from each reference position.
hfrac = xoff - floor(xoff); % Fractional offset of xoff relative to integer location
vfrac = yoff - floor(yoff); % Fractional offset of yoff relative to integer location
orient = fix(orient)+1; % Orientations start at 0 degrees but arrays start
% with index 1.
% Now run through the image interpolating grey values on each side
% of the centre pixel to be used for the non-maximal suppression.
for row = (iradius+1):(rows - iradius)
for col = (iradius+1):(cols - iradius)
or = orient(row,col); % Index into precomputed arrays
x = col + xoff(or); % x, y location on one side of the point in question
y = row - yoff(or);
fx = floor(x); % Get integer pixel locations that surround location x,y
cx = ceil(x);
fy = floor(y);
cy = ceil(y);
tl = inimage(fy,fx); % Value at top left integer pixel location.
tr = inimage(fy,cx); % top right
bl = inimage(cy,fx); % bottom left
br = inimage(cy,cx); % bottom right
upperavg = tl + hfrac(or) * (tr - tl); % Now use bilinear interpolation to
loweravg = bl + hfrac(or) * (br - bl); % estimate value at x,y
v1 = upperavg + vfrac(or) * (loweravg - upperavg);
if inimage(row, col) > v1 % We need to check the value on the other side...
x = col - xoff(or); % x, y location on the `other side' of the point in question
y = row + yoff(or);
fx = floor(x);
cx = ceil(x);
fy = floor(y);
cy = ceil(y);
tl = inimage(fy,fx); % Value at top left integer pixel location.
tr = inimage(fy,cx); % top right
bl = inimage(cy,fx); % bottom left
br = inimage(cy,cx); % bottom right
upperavg = tl + hfrac(or) * (tr - tl);
loweravg = bl + hfrac(or) * (br - bl);
v2 = upperavg + vfrac(or) * (loweravg - upperavg);
if inimage(row,col) > v2 % This is a local maximum.
im(row, col) = inimage(row, col); % Record value in the output image.
end
end
end
end