It seems like you're asking for a Python code using OpenCV and NumPy libraries. Here's a simple step-by-step guide:

1. Import the necessary libraries:
```python
import cv2
import numpy as np
import matplotlib.pyplot as plt
```

2. Read the input image:
```python
img = cv2.imread('input.jpg')
```

3. Convert the RGB image to grayscale:
```python
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
```

4. Display the grayscale image:
```python
cv2.imshow('Grayscale Image', gray)
cv2.waitKey(0)
cv2.destroyAllWindows()
```

5. Compute the FFT of the grayscale image:
```python
f = np.fft.fft2(gray)
fshift = np.fft.fftshift(f)
```

6. Display the FFT output:
```python
magnitude_spectrum = 20*np.log(np.abs(fshift))
plt.figure(), plt.imshow(magnitude_spectrum, cmap = 'gray')
plt.title('Magnitude Spectrum'), plt.xticks([]), plt.yticks([])
plt.show()
```

7. Display the normalized intensity value of pixel coordinates:
```python
norm_image = cv2.normalize(gray, None, alpha = 0, beta = 1, norm_type = cv2.NORM_MINMAX, dtype = cv2.CV_32F)
print('Normalized intensity values:', norm_image)
```

Please replace 'input.jpg' with your actual image file path. Also, note that the FFT output and the normalized intensity values are displayed in the console.

Question

It seems like you're asking for a Python code using OpenCV and NumPy libraries. Here's a simple step-by-step guide:

1. Import the necessary libraries:
```python
import cv2
import numpy as np
import matplotlib.pyplot as plt
```

2. Read the input image:
```python
img = cv2.imread('input.jpg')
```

3. Convert the RGB image to grayscale:
```python
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
```

4. Display the grayscale image:
```python
cv2.imshow('Grayscale Image', gray)
cv2.waitKey(0)
cv2.destroyAllWindows()
```

5. Compute the FFT of the grayscale image:
```python
f = np.fft.fft2(gray)
fshift = np.fft.fftshift(f)
```

6. Display the FFT output:
```python
magnitude_spectrum = 20*np.log(np.abs(fshift))
plt.figure(), plt.imshow(magnitude_spectrum, cmap = 'gray')
plt.title('Magnitude Spectrum'), plt.xticks([]), plt.yticks([])
plt.show()
```

7. Display the normalized intensity value of pixel coordinates:
```python
norm_image = cv2.normalize(gray, None, alpha = 0, beta = 1, norm_type = cv2.NORM_MINMAX, dtype = cv2.CV_32F)
print('Normalized intensity values:', norm_image)
```

Please replace 'input.jpg' with your actual image file path. Also, note that the FFT output and the normalized intensity values are displayed in the console.

Knowee AI · Accepted Answer