Neighborhood Filters

Five questions. Choose one answer for each, then submit to see your score and explanations.

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1. Which explanation matches build a filter from kernel weights?A. Padding or boundary rules define the missing neighbors outside the image.B. A kernel assigns weights to nearby pixel values to compute each output.C. Gaussian smoothing averages neighbors with distance-dependent weights, with scale set by its spread.D. A median filter chooses the middle neighborhood value, unlike a weighted average.

2. Which explanation matches boundary rules change the result?A. Padding or boundary rules define the missing neighbors outside the image.B. A kernel assigns weights to nearby pixel values to compute each output.C. Gaussian smoothing averages neighbors with distance-dependent weights, with scale set by its spread.D. A median filter chooses the middle neighborhood value, unlike a weighted average.

3. Which explanation matches gaussian smoothing and scale?A. A kernel assigns weights to nearby pixel values to compute each output.B. Padding or boundary rules define the missing neighbors outside the image.C. A median filter chooses the middle neighborhood value, unlike a weighted average.D. Gaussian smoothing averages neighbors with distance-dependent weights, with scale set by its spread.

4. For boundary rules change the result, which result or action fits this practical case: The filter changes the pixels at the left edge of a photograph.A. Average three values 10, 20, and 30 with equal weights to obtain 20.B. Compare a narrow blur that retains the scratch with a wider blur that erases it.C. Compare zero padding with reflecting the edge for the same smoothing kernel.D. For neighboring values 10, 11, and 250, the median is 11.

5. For median and edge-preserving choices, which result or action fits this practical case: A few isolated bright specks appear over a clean metal surface.A. Average three values 10, 20, and 30 with equal weights to obtain 20.B. For neighboring values 10, 11, and 250, the median is 11.C. Compare zero padding with reflecting the edge for the same smoothing kernel.D. Compare a narrow blur that retains the scratch with a wider blur that erases it.

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Neighborhood Filters

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