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/external/opencv3/doc/py_tutorials/py_imgproc/py_transforms/py_fourier_transform/
Dpy_fourier_transform.markdown17 **2D Discrete Fourier Transform (DFT)** is used to find the frequency domain. A fast algorithm
18 called **Fast Fourier Transform (FFT)** is used for calculation of DFT. Details about these can be
25 (or \f$[0,N]\f$ for N-point DFT). You can consider an image as a signal which is sampled in two
75 pass filtering and reconstruct the image, ie find inverse DFT. For that you simply remove the low
103 region of the spectrum. Anyway we have seen how to find DFT, IDFT etc in Numpy. Now let's see how to
140 So, now we have to do inverse DFT. In previous session, we created a HPF, this time we will see how
153 # apply mask and inverse DFT
173 Performance Optimization of DFT
176 Performance of DFT calculation is better for some array size. It is fastest when array size is power
179 the array to any optimal size (by padding zeros) before finding DFT. For OpenCV, you have to
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/external/opencv3/doc/tutorials/core/discrete_fourier_transform/
Ddiscrete_fourier_transform.markdown49 (*DFT*). You'll want to use this whenever you need to determine the structure of an image from a
52 -# **Expand the image to an optimal size**. The performance of a DFT is dependent of the image
82 complex (imaginary - *Im*) part. The results of a DFT are complex numbers. The magnitude of a
83 DFT is:
85 \f[M = \sqrt[2]{ {Re(DFT(I))}^2 + {Im(DFT(I))}^2}\f]
89 split(complexI, planes); // planes[0] = Re(DFT(I), planes[1] = Im(DFT(I))
/external/opencv3/modules/core/src/
Ddxt.cpp526 DFT( const Complex<T>* src, Complex<T>* dst, int n, in DFT() function
1038 DFT( _dst, _dst, n, nf, factors, itab, wave, in RealDFT()
1050 DFT( (Complex<T>*)src, (Complex<T>*)dst, n2, nf - (factors[0] == 1), in RealDFT()
1169 DFT( _dst, _dst, n, nf, factors, itab, wave, in CCSIDFT()
1249 DFT( (Complex<T>*)dst, (Complex<T>*)dst, n2, in CCSIDFT()
1451 DFT(src, dst, n, nf, factors, itab, wave, tab_size, spec, buf, flags, scale); in DFT_32f()
1460 DFT(src, dst, n, nf, factors, itab, wave, tab_size, spec, buf, flags, scale); in DFT_64f()
/external/llvm/lib/Transforms/Utils/
DSimplifyCFG.cpp494 SmallVector<Value *, 8> DFT; in gather() local
497 DFT.push_back(V); in gather()
499 while(!DFT.empty()) { in gather()
500 V = DFT.pop_back_val(); in gather()
505 DFT.push_back(I->getOperand(1)); in gather()
506 DFT.push_back(I->getOperand(0)); in gather()
/external/opencv3/doc/tutorials/introduction/windows_install/
Dwindows_install.markdown72 of color conversion, Haar training and DFT functions of the OpenCV library. Watch out, since