Homec4science
Diffusion Motion correction paper (translation_to_python) Browse

R6289/code/external/utils/partial_deriv.m
4534f6e606c9translation_to_python

Last Change
Raw File

partial_deriv.m
View Options

function [It, Ix, Iy] = partial_deriv(images, uv_prev, interpolation_method, deriv_filter, b)
%PARTIAL_DERIV Spatio-temporal derivatives
% P = PARTIAL_DERIV(IMAGES, INIT) computes the spatio-temporal derivatives
%
% Author: Deqing Sun, Department of Computer Science, Brown University
% Contact: dqsun@cs.brown.edu
% $Date: 2007-11-30 $
% $Revision $
%
% Copyright 2007-2010, Brown University, Providence, RI. USA
%
% All Rights Reserved
%
% All commercial use of this software, whether direct or indirect, is
% strictly prohibited including, without limitation, incorporation into in
% a commercial product, use in a commercial service, or production of other
% artifacts for commercial purposes.
%
% Permission to use, copy, modify, and distribute this software and its
% documentation for research purposes is hereby granted without fee,
% provided that the above copyright notice appears in all copies and that
% both that copyright notice and this permission notice appear in
% supporting documentation, and that the name of the author and Brown
% University not be used in advertising or publicity pertaining to
% distribution of the software without specific, written prior permission.
%
% For commercial uses contact the Technology Venture Office of Brown University
%
% THE AUTHOR AND BROWN UNIVERSITY DISCLAIM ALL WARRANTIES WITH REGARD TO
% THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND
% FITNESS FOR ANY PARTICULAR PURPOSE. IN NO EVENT SHALL THE AUTHOR OR
% BROWN UNIVERSITY BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL
% DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR
% PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
% ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF
% THIS SOFTWARE.
if nargin == 2
interpolation_method = 'cubic';
end;
if nargin == 4
h = deriv_filter;
else
h = [1 -8 0 8 -1]/12; % used in Wedel etal "improved TV L1"
end;
if nargin < 5
b = 0.5; %blending ratio
end;
H = size(images, 1);
W = size(images, 2);
[x,y] = meshgrid(1:W,1:H);
x2 = x + uv_prev(:,:,1);
y2 = y + uv_prev(:,:,2);
% Record out of boundary pixels
B = (x2>W) | (x2<1) | (y2>H) | (y2<1);
if size(images, 4) ~= 1
B = repmat(B, [1 1 size(images, 3)]);
end;
if size(images, 4) == 1
img1 = images(:,:,1);
img2 = images(:,:,2);
else
img1 = images(:,:,:,1);
img2 = images(:,:,:,2);
end;
if strcmp(interpolation_method, 'bi-cubic')
%h = [-0.5, 0, 0.5]; % consistent with bi-cubic interpolation
% Bicubic interpolation
if nargout == 1
if size(images, 4) == 1
% gray-level
warpIm = interp2_bicubic(images(:,:,2),x2,y2, h);
else
% color
warpIm = zeros(size(images(:,:,:,1)));
for j = 1:size(images,3)
warpIm(:,:,j) = interp2_bicubic(images(:,:,j, 2),x2,y2, h);
end;
end;
elseif nargout == 3
if size(images, 4) == 1
% gray-level
[warpIm Ix Iy] = interp2_bicubic(images(:,:,2),x2,y2, h);
else
% color
warpIm = zeros(size(images(:,:,:,1)));
Ix = warpIm;
Iy = warpIm;
for j = 1:size(images,3)
[warpIm(:,:,j) Ix(:,:,j) Iy(:,:,j)] = interp2_bicubic(images(:,:,j,2),x2,y2, h);
end;
end;
else
error('partial_deriv: number of output wrong!');
end;
indx = isnan(warpIm);
if size(images, 4) == 1
It = warpIm - images(:,:,1);
else
It = warpIm - images(:,:,:,1);
end;
% Disable those out-of-boundary pixels in warping
It(indx) = 0;
if nargout == 3
% Temporal average
I1x = imfilter(img1, h, 'corr', 'symmetric', 'same'); %
I1y = imfilter(img1, h', 'corr', 'symmetric', 'same');
% b = 0.6; % recommended in Wedal etal "improved TV-L1" 2008
% b = 0.5;
% b = 1;
Ix = b*Ix+(1-b)*I1x;
Iy = b*Iy+(1-b)*I1y;
Ix(indx) = 0;
Iy(indx) = 0;
end;
elseif strcmp(interpolation_method, 'bi-linear') || strcmp(interpolation_method, 'cubic')
if strcmp(interpolation_method, 'bi-linear')
method = 'linear';
else
method = 'cubic';
end;
% Matlab built-in
if size(images, 4) == 1
% Gray-level
warpIm = interp2(x,y,images(:,:,2),x2,y2,method);
It = warpIm - images(:,:,1);
else
% Color
warpIm = zeros(size(images(:,:,:,1)));
for j = 1:size(images,3)
warpIm(:,:,j) = interp2(x,y,images(:,:,j,2),x2,y2,method, NaN);
end;
It = warpIm - images(:,:,:,1);
end;
% spline-based bicubic interpolation code with incorrect derivatives (below)
% if size(images, 4) == 1
% % gray-level
% warpIm = interp2_bicubic(images(:,:,2),x2,y2, h);
% It = warpIm - images(:,:,1);
% else
% % color
% warpIm = zeros(size(images(:,:,:,1)));
% for j = 1:size(images,3)
% warpIm(:,:,j) = interp2_bicubic(images(:,:,j, 2),x2,y2, h);
% end;
% It = warpIm - images(:,:,:,1);
% end;
if nargout == 3
% First compute derivative then warp
I2x = imfilter(img2, h, 'corr', 'symmetric', 'same');
I2y = imfilter(img2, h', 'corr', 'symmetric', 'same');
if size(images, 4) == 1
% Gray-level
Ix = interp2(x,y,I2x,x2,y2,method);
Iy = interp2(x,y,I2y,x2,y2,method);
% % spline-based bicubic interpolation code with incorrect derivatives
% Ix = interp2_bicubic(I2x,x2,y2, h);
% Iy = interp2_bicubic(I2y,x2,y2, h);
else
% Color
Ix = zeros(size(images(:,:,:,1)));
Iy = Ix;
for j = 1:size(images,3)
Ix(:,:,j) = interp2(x,y,I2x(:,:,j),x2,y2,method);
Iy(:,:,j) = interp2(x,y,I2y(:,:,j),x2,y2,method);
end;
end;
% warp then derivative
% if size(images, 4) == 1
% tmp = images(:,:,1);
% else
% tmp = images(:,:,:,1);
% end;
% warpIm(B) = tmp(B);
% Ix = imfilter(warpIm, h, 'corr', 'symmetric', 'same'); %
% Iy = imfilter(warpIm, h', 'corr', 'symmetric', 'same');
% end of warp then derivative
% Temporal average
I1x = imfilter(img1, h, 'corr', 'symmetric', 'same'); %
I1y = imfilter(img1, h', 'corr', 'symmetric', 'same');
% b = 0.6; % recommended in Wedal etal "improved TV-L1" 2008
% b = 0.5;
Ix = b*Ix+(1-b)*I1x;
Iy = b*Iy+(1-b)*I1y;
end;
% Disable those out-of-boundary pixels in warping
It(B) = 0;
if nargout == 3
Ix(B) = 0;
Iy(B) = 0;
end;
else
error('partial_deriv: unknown interpolation method!');
end;
c4science · Help