Image Processing
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Hi 2 all I have 16x16 image i want to convert this to 128x128 image (that means for every 16 bit it must replicate to 8x8 of this same bit value) Please clarify this Thx in advance
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Image Analyst
2011-8-20
Another way to do it, using the Image Processing Toolbox:
m128 = imresize(m16, 8, 'nearest');
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Sean de Wolski
2011-8-22
It's the name of the image variable that will be 128x128, hence the descriptive numbering.
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Sean de Wolski
2011-8-20
New_Image = kron(your_image,ones(8));
Kronecker Tensor Product
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Sean de Wolski
2011-8-22
It's probably just dirt from the trail. I'll get a bigger picture! And yes, she got Firedog 4.2.
Vivek Bhadouria
2011-8-22
Use this piece of code
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This program is used to zoom or shrink an image
% Input:image B3: gray-image or RGB image
% p: ratio, zooming (p>1), shrink(p<1)
% m: mode; =0:(default) nearest neighbor interpolation
% =1: Bilinear interpolation
% =2: Bicubic interpolation
% Output: image A3 % A3 = imageresize(B3,p,m);
%Vivek Singh Bhadouria, NIT-Agartala
%India, 9 August 2011, 01:05 AM
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function A3 = imageresize(B3,p,m)
B3=im2double(B3);
error(nargchk(2, 3, nargin, 'struct'));
if nargin < 3, m = 0; end
dimB = length(size(B3));
if dimB== 2 % GRAY-IMAGE INPUT:
A3 = gray_resize(B3,p,m);
elseif dimB== 3 % COLOR RGB-IMAGE INPUT:
AR = gray_resize(B3(:,:,1),p,m);
AG = gray_resize(B3(:,:,2),p,m);
AB = gray_resize(B3(:,:,3),p,m);
A3 = zeros([size(AR) 3]);
A3(:,:,1) = AR;
A3(:,:,2) = AG;
A3(:,:,3) = AB;
else
error('Improper input image');
end
%**************************************************%
%==================================================%
% Sub-Function: Resize a gray-image
% Same input argument with imageresize()
function A = gray_resize(B,p,m)
% Initialize new-grid and output
[N,M] = size(B);
xp = 1:1/p:N+1/p; yp = 1:1/p:M+1/p;
A = zeros(length(xp),length(yp));
% Symmetric Padding
npad = 3;
B = sym_pad(B,npad);
switch m
case 0 % Nearest neighbor interpolation
U = round(xp); V = round(yp);
U(find(U<1)) = 1; V(find(V<1)) = 1;
U(find(U>N)) = N; V(find(V>M)) = M;
A = B(U+npad,V+npad);
case 1 % Bilinear interpolation
% Floor of (xp,yp)
xf = floor(xp); yf = floor(yp);
% Distance to top-left neighbors
[XF,YF] = ndgrid(xf,yf);
[XP,YP] = ndgrid(xp,yp);
u = XP - XF; v = YP - YF;
% Change xf, yf for new padding image
xf = xf + npad; yf = yf + npad;
% Interpolation
A = (1-u).*(1-v).*B(xf,yf) + ...
(1-u).*v .*B(xf,yf+1) + ...
u .*(1-v) .*B(xf+1,yf) + ...
u .*v .*B(xf+1,yf+1);
case 2
% Floor of (xp,yp)
xf = floor(xp);yf = floor(yp);
% Distance to top-left neighbors
[XF,YF] = ndgrid(xf,yf);
[XP,YP] = ndgrid(xp,yp);
u = XP - XF; v = YP - YF;
% Change xf, yf for new padding image
xf = xf + npad; yf = yf + npad;
% Interpolation: 16 neighbors
for i = -1:2
for j = -1:2
if i==-1, sgi = -1; else sgi = 1; end
if j==-1, sgj = -1; else sgj = 1; end
A = A + mex_hat(sgi*(i-u)).*mex_hat(sgj*(j-v)).*B(xf+i,yf+j);
end
end
otherwise
error('Undefined Interpolation method');
end
%**************************************************%
%==================================================%
% Sub-Function: Mexican-hat kernel
function hx = mex_hat(x)
hx = zeros(size(x));
x = abs(x);
ind1 = find(x<=1); ind2 = find(x>1 & x<=2);
hx(ind1) = 1 - 2*x(ind1).^2 + x(ind1).^3;
hx(ind2) = 4 - 8*x(ind2) + 5*x(ind2).^2 - x(ind2).^3;
% END of sub-function
%==================================================%
% Sub-Function: symmetric padding, by default 2 pixels
% Input: gray image
function Bp = sym_pad(B,n)
Bp = zeros(size(B)+2*n);
Bp(n+1:end-n,n+1:end-n) = B;
% Padding symmetrically 4 boundaries
Bp(n:-1:1,n+1:end-n) = B(1:n,:);
Bp(n+1:end-n,n:-1:1) = B(:,1:n);
Bp(end-n+1:end,n+1:end-n) = B(end:-1:end-n+1,:);
Bp(n+1:end-n,end-n+1:end) = B(:,end:-1:end-n+1);
% END of sub-function
%==================================================%
HAPPY TO HELP FOR SCIENTIFIC NOBLE CAUSE
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