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• Switching from Debug into Release Mode with VS2010 as IDE and Intel C++ Compiler 13

  - by Drazick

  I have a code of a Plug In from an SDK. The code is in Debug Mode. I use Intel Compiler which only applies optimizations in Release Mode. Under configuration manager of the project only "Debug" mode is defined. How could I switch to "Release" mode and enable all Intel Compiler's optimizations? If I enable them on debug mode nothing is applied (Empty Report). I couldn't find the trick to do so. Thank You.

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• Noise Estimation / Noise Measurement in Image

  - by Drazick

  Hello. I want to estimate the noise in an image. Let's assume the model of an Image + White Noise. Now I want to estimate the Noise Variance. My method is to calculate the Local Variance (3*3 up to 21*21 Blocks) of the image and then find areas where the Local Variance is fairly constant (By calculating the Local Variance of the Local Variance Matrix). I assume those areas are "Flat" hence the Variance is almost "Pure" noise. Yet I don't get constant results. Is there a better way? Thanks.

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• 1D Function into 2D Function Interpolation

  - by Drazick

  Hello. I have a 1D function which I want to interpolate into 2D function. I know the function should have "Polar Symmetry". Hence I use the following code (Matlab Syntax): Assuming the 1D function is LSF of the length 15. [x, y] = meshgrid([-7:7]); r = sqrt(x.^2 + y.^2); PSF = interp1([-7:7], LSF, r(:)); % Sometimes using 'spline' option, same results. PSF = reshape(PSF, [7, 7]); I have few problems: 1. Got some overshoot at the edges (As there some Extrapolation). 2. Can't enforce some assumptions (Monotonic, Non Negative). Is there a better Interpolation method for those circumstances? I couldn't find "Lanczos" based interpolation I can use the same way as interp1 (For a certain vector of points, in "imresize" you can only set the length). Is there such function anywhere? Has anyone encountered a function which allows enforcing some assumptions (Monotonically Decreasing, Non Negative, etc..). Thanks.

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• Interpolating 1D Gaussian into 2D Gaussian

  - by Drazick

  Let's say I have a 1D Gaussian function. Its length is 600 for that matter. I want to Interpolate it into 2D Gaussian of the size 600 X 600. This is the code I wrote (OTFx is the Gaussian Function, OTF - 2d Interpolated Function): [x, y] = meshgrid([-300:299], [-300:299]); r = sqrt((x .^ 2) + (y .^ 2)); OTF = interp1([-300:299], OTFx, r(:), 'spline'); OTF = reshape(OTF, [600, 600]); The problem is I get Overshoot at the end: How can I prevent it? Is there better Interpolating algorithm for Monotonic Descending Functions?

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