SciPy - Image Processing (scipy.ndimage)
Which combination of SciPy ndimage filters is most effective for first reducing noise and then detecting edges in a grayscale image?
Which combination of SciPy ndimage filters is most effective for first reducing noise and then detecting edges in a grayscale image?
hard📝 Application Q8 of 15
Step-by-Step Solution
Solution:
Step 1: Noise reduction
Median filters are effective at removing salt-and-pepper noise without blurring edges.Step 2: Edge detection
Sobel filters highlight edges by calculating gradients after noise has been reduced.Final Answer:
Apply a median filter followed by a Sobel filter -> Option BQuick Check:
Noise reduction before edge detection improves results [OK]
Quick Trick: Remove noise first, then detect edges [OK]
Common Mistakes:
- Applying edge detection before noise removal
- Using Gaussian filter after Sobel which blurs edges
- Confusing filter order for best results
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