![]() function min, max fminmax (f, lowerbound, upperbound) min fminbnd (f, lowerbound, upperbound) max fminbnd. To get the max you could just use the negative of your function handle. Upload an image if you want further advice. You could use the already existing function x fminbnd (fun, x1, x2) which gives you the min for a function handle fun in the range of x1 and x2. For certain other cases (radiology and fluorescence) you should do subtraction. Finally, division is the right way to do it in most cases. Choose a web site to get translated content where available and see local events and offers. Find the treasures in MATLAB Central and discover how the community can help you Start Hunting. Do you have a uniform background that you can image? Or all you have is the image with your scene and illumination combined? If, unfortunately, you have the latter case, you can either try homomorphic filtering (basically assuming the light pattern is a very low pass filtered version of your scene) or try to find "holes" in your scene that is pure background and then try to fit a nice smooth model, like a 2D polynomial, to them. Use the second return argument of max and min: minValue, indexOfMinValue min(d). But even then, there are flaws with that method such that you will increase the noise and have quantization/posterization errors. I do background correction all the time and this would not be a good way of getting the background unless your background was uniform and had small light-colored dust on it. ![]() It is not a way to get the illumination pattern that I've ever heard of. For example, the following code produces a row vector M that contains the maximum value of each column of A, which is 3 for the first column and 4 for the second column. For an input A that contains symbolic expression, the symbolic max function returns an unevaluated expression that is reduced by eliminating arguments that do not represent maximum values. If A is a matrix, then max(A) is a row vector containing the maximum value of each column. Note that deriving is not that simple since the zero locations falls between pixels, and zero crossing in a 2d image is more complected than a 1d signal. ![]() In the example below the results should be two lines at the bottom, and some local peaks at the top. Doing a max filter on the output of the min filter is called a morphological opening and is done by imopen(). The 'min' and 'max' functions in MATLAB return the index of the minimum and maximum values, respectively, as an optional second output argument. If A is a vector, then max(A) returns the maximum of A. EDIT: Maximum and minimum in terms of derivative, not absolute max/min.
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