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To perform the least square method for each pixel of each image, you want to read finally its optimized value as an image. Model function is known, t and y are also known. When it comes to the matrix, such as 64 * 64 do not know how should I how to set the function, also, does not work is the calculation of each error occurs pixels.
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x1 = double (imread ('1.png'));
x2 = double (imread ('2.png'));
x3 = double (imread ( '3.png'));
t = [zeros (size (x1)) repmat (20, size (x1)) repmat (30, size (x1))];
y = [.. ones (size (x1)) x2 / x1 x3 / x1];
f = (exp (-x (1) * t) + exp (- (x (1) + x (2)) * t)) - y;
% In the case of the model function,
You have exceeded the maximum variable size that are available in the program.
Error lsqncommon (line 139)
Jstr = sparse (ones (Jrows, Jcols));
Error lsqnonlin (line 237)
[xCurrent, Resnorm, FVAL, EXITFLAG, OUTPUT, LAMBDA, JACOB] = ...
Error lm (line 31)
[x, resnorm, residual, exitflag, output] = lsqnonlin (@ myfun1, x0);% Invoke optimizer
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do not know is that the "use of lsqnonlin function for each pixel," "make a continuously calculated for each pixel." Please be taught kindly.
