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Why can fourier transform be used for image recognization while being sensitive to noises?


Why can fourier transform be used for image recognization while being sensitive to noises?

By : futguy11
Date : November 22 2020, 07:01 PM
like below fixes the issue Update to actually answer the question you asked... :) Pre-process the image with a non-linear filter to suppress the salt & pepper noise. Median filter maybe?
Basic lesson on FFTs on matched filters follows...
code :


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Fourier transform of an image in EmguCV

Fourier transform of an image in EmguCV


By : user3620285
Date : March 29 2020, 07:55 AM
may help you . From my answer Fourier Transform + emgucv
The function you are after is CvInvoke.cvDFT it is technically calling the opencv method but it should be what your after
code :
Image<Gray, float> image = new Image<Gray, float>(open.FileName);
IntPtr complexImage = CvInvoke.cvCreateImage(image.Size, Emgu.CV.CvEnum.IPL_DEPTH.IPL_DEPTH_32F, 2);

CvInvoke.cvSetZero(complexImage);  // Initialize all elements to Zero
CvInvoke.cvSetImageCOI(complexImage, 1);
CvInvoke.cvCopy(image, complexImage, IntPtr.Zero);
CvInvoke.cvSetImageCOI(complexImage, 0);

Matrix<float> dft = new Matrix<float>(image.Rows, image.Cols, 2);
CvInvoke.cvDFT(complexImage, dft, Emgu.CV.CvEnum.CV_DXT.CV_DXT_FORWARD, 0);

//The Real part of the Fourier Transform
Matrix<float> outReal = new Matrix<float>(image.Size);
//The imaginary part of the Fourier Transform
Matrix<float> outIm = new Matrix<float>(image.Size);
CvInvoke.cvSplit(dft, outReal, outIm, IntPtr.Zero, IntPtr.Zero);

//Show The Data       
CvInvoke.cvShowImage("Real", outReal);
CvInvoke.cvShowImage("Imaginary ", outIm);
How to colourize Fourier transform if image

How to colourize Fourier transform if image


By : Gl Xuan
Date : March 29 2020, 07:55 AM
will be helpful for those in need I propose the following approach. First, choose a maximum value (the one to represent "red") and scale all values in the [0, 1] interval. Next, use this value for the hue and use a HSL to RGB transformation. The Python code would look like this:
code :
import colorsys
from PIL import Image, ImageDraw

w = 400
h = 20
im = Image.new("RGB", (w, h))
draw = ImageDraw.Draw(im)

for x in range(0, 100):
    value = float(x)/100

    r, g, b = colorsys.hsv_to_rgb(1-value*3/4-0.33, 1, 1)
    color = int(r*255), int(g*255), int(b*255)
    draw.rectangle((x * 4, 0, (x + 1) * 4, h), color, color)

im.save('example.png' , 'png')
C++ Image 2D Fast Fourier Transform

C++ Image 2D Fast Fourier Transform


By : เอ สอสิ นมภ
Date : March 29 2020, 07:55 AM
wish helps you I found out that the answer was an incorrect implementation of multiplication operator in my Complex class.
code :
Complex Complex::operator*(const Complex& a)
{
    Complex number;
    double RP = realPart * a.getRP() - imaginaryPart * a.getIP(); // this line was wrong
    double IP = realPart * a.getIP() + imaginaryPart * a.getRP();
    number.setRP(RP);
    number.setIP(IP);
    return number;
}
How do I go from redundancy-free Fourier Transform (e.g. PyTorch) to redundant (full) Fourier Transform?

How do I go from redundancy-free Fourier Transform (e.g. PyTorch) to redundant (full) Fourier Transform?


By : John Smith
Date : March 29 2020, 07:55 AM
it should still fix some issue I finally succeeded in using np.meshgrid properly to fill in the relevant data. We can use ranges for the entire row range and the missing part of the column range to only fill these indices with the appropriate data.
code :
import numpy as np
np.random.seed(0)

N     = 10
image = np.random.rand(N, N)
h, w  = image.shape

ft           = np.fft.rfft2(image)
ft_reference = np.fft.fft2(image)
ft_full      = np.zeros_like(image, dtype=np.complex128)
ft_full[:ft.shape[0], :ft.shape[1]] = ft

X, Y          = np.meshgrid(range(h), range(w // 2 + 1, w), indexing='ij')
ft_full[X, Y] = ft_full[-X, -Y].conj()
print(np.allclose(ft_full, ft_reference))
How to apply Fourier Transform to a color image and inverse Fourier Transform to a gray image?

How to apply Fourier Transform to a color image and inverse Fourier Transform to a gray image?


By : MrPhys
Date : March 29 2020, 07:55 AM
I wish this help you No, that does not work.
If you want to apply a convolution to a color image, you should apply the convolution to each channel independently.
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