[Solved] Given the code below, what will be the output array after applying the Gaussian filter?... Given the code below, what will be the output array after applying the Gaussian filter? | SciPy

SciPy - Image Processing (scipy.ndimage)

Given the code below, what will be the output array after applying the Gaussian filter?

import numpy as np
from scipy.ndimage import gaussian_filter

image = np.array([[0, 0, 0],
                  [0, 10, 0],
                  [0, 0, 0]])
filtered = gaussian_filter(image, sigma=1)
print(np.round(filtered, 2))

A[[0.46 1.23 0.46] [1.23 2.99 1.23] [0.46 1.23 0.46]]

B[[0 0 0] [0 10 0] [0 0 0]]

C[[2.5 2.5 2.5] [2.5 2.5 2.5] [2.5 2.5 2.5]]

D[[0.1 0.1 0.1] [0.1 10 0.1] [0.1 0.1 0.1]]

Step-by-Step Solution

Solution:

Step 1: Understand Gaussian filter effect on sparse image
The single bright pixel (10) will blur into neighbors, spreading intensity smoothly.
Step 2: Calculate approximate blurred values
Using sigma=1, the center pixel reduces from 10 to about 3, neighbors get values around 1.2 to 0.46.
Final Answer:
[[0.46 1.23 0.46] [1.23 2.99 1.23] [0.46 1.23 0.46]] -> Option A
Quick Check:
Blur spreads intensity smoothly = [[0.46 1.23 0.46] [1.23 2.99 1.23] [0.46 1.23 0.46]] [OK]

Quick Trick: Gaussian blur spreads bright pixels softly to neighbors [OK]

Common Mistakes:

Expecting no change in array
Assuming uniform average instead of weighted blur
Misreading sigma effect as sharpening

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More SciPy Quizzes

Given the code below, what will be the output array after applying the Gaussian filter?

Step 1: Understand Gaussian filter effect on sparse image

Step 2: Calculate approximate blurred values

Final Answer:

Quick Check:

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