[Solved] You have a noisy 2D image array with salt-and-pepper noise. Which filter and parameters would best reduce noise while... Which filter and parameters would best reduce noise while preserving edges? | SciPy

SciPy - Image Processing (scipy.ndimage)

You have a noisy 2D image array with salt-and-pepper noise. Which filter and parameters would best reduce noise while preserving edges?

import numpy as np
from scipy.ndimage import median_filter, uniform_filter

image = np.array([[10, 10, 10, 10],
                  [10, 255, 10, 10],
                  [10, 10, 10, 10],
                  [10, 10, 10, 10]])

AUse median_filter with size=3 to remove salt-and-pepper noise

BUse uniform_filter with size=3 to blur the image

CUse median_filter with size=1 to keep image unchanged

DUse uniform_filter with size=1 to sharpen edges

Step-by-Step Solution

Solution:

Step 1: Understand noise type and filter effects
Salt-and-pepper noise is best removed by median filters because they replace each pixel with the median of neighbors, preserving edges.
Step 2: Evaluate filter choices and parameters
Median_filter with size=3 covers neighbors and removes noise spikes. Uniform_filter averages and blurs edges, not ideal here. Size=1 means no change.
Final Answer:
Use median_filter with size=3 to remove salt-and-pepper noise -> Option A
Quick Check:
Median filter + size=3 removes salt-and-pepper noise [OK]

Quick Trick: Median filter removes salt-and-pepper noise best [OK]

Common Mistakes:

Using uniform filter which blurs edges
Using size=1 which does nothing
Confusing noise types and filter effects

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More SciPy Quizzes

You have a noisy 2D image array with salt-and-pepper noise. Which filter and parameters would best reduce noise while preserving edges?

Step 1: Understand noise type and filter effects

Step 2: Evaluate filter choices and parameters

Final Answer:

Quick Check:

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