ifft

I am attempting to recreate a classical shape from shading algorithm seen in the Trucco/Verri text "Introductory Techniques for 3d Computer Vision", but I am having a hard time understanding the fft function in matlab. Essentially, I need to use the integrability constraint to get the depth (Z) of an image. I am not sure when to use fftshift or not in this scenario. Here is the code I have so far. Based on http://www.mathworks.com/matlabcentral/newsreader/view_thread/285244 I basically wrapped all my fft2s in fftshifts, but I don't think this is the correct usage. Could someone please explain

I am trying to filter some data based on the the following code using Arduino FFT library for FFT (fast Fourier transform) /* fft_adc_serial.pde guest openmusiclabs.com 7.7.14 example sketch for testing the fft library. it takes in data on ADC0 (Analog0) and processes them with the fft. the data is sent out over the serial port at 115.2kb. */ #define LOG_OUT 1 // use the log output function #define FFT_N 256 // set to 256 point fft #include <FFT.h> // include the library void setup() { Serial.begin(115200); // use the serial port TIMSK0 = 0; // turn off timer0 for lower jitter ADCSRA = 0xe5; /

I have convoluted an image I created in matlab with a 2D Gaussian function which I have also defined in matlab and now I am trying to deconvolve the resultant matrix to see if I get the 2D Gaussian function back using the fft2 and ifft2 commands. However the matrix I get as a result is incorrect (to my knowledge). Here is the code for what I have done thus far: % Code for input image (img) [300x300 array] N = 100; t = linspace(0,2*pi,50); r = (N-10)/2; circle = poly2mask(r*cos(t)+N/2+0.5, r*sin(t)+N/2+0.5,N,N); img = repmat(circle,3,3); % Code for 2D Gaussian Function with c = 0 sig = 1/64 (Z)