Spatial Filtering Fundamentals Quiz

Choose a study mode

Play Quiz
Study Flashcards
Spaced Repetition
Chat to Lesson

Podcast

Play an AI-generated podcast conversation about this lesson
Download our mobile app to listen on the go
Get App

Questions and Answers

What is the main difference between spatial correlation and spatial convolution?

  • The padding method used
  • The sum of products computation
  • The rotation angle of the kernel (correct)
  • The size of the kernel

How does spatial convolution handle an edge of the image when the mask partly falls outside the image?

  • Rotate the kernel
  • Ignore the edges
  • Replicate padding
  • Mirror padding/symmetric (correct)

What happens if a kernel used in spatial filtering is asymmetric about its center?

  • Spatial correlation and convolution will give different results (correct)
  • The filtering process fails
  • The output is larger than the original
  • The output is smaller than the original

Which type of filter is used to enhance edges and high-frequency components in an image?

<p>Highpass filter (B)</p> Signup and view all the answers

In linear spatial filtering, what does a highpass filter mainly emphasize in an image?

<p>Details and edges (B)</p> Signup and view all the answers

What does zero padding refer to in spatial filtering?

<p>Setting all values outside the image to zero (B)</p> Signup and view all the answers

What is the purpose of smoothing filters in image processing?

<p>To smooth out false contours caused by insufficient intensity levels (C)</p> Signup and view all the answers

What is the key difference between high frequency and low frequency components in an image?

<p>High frequency components have large changes in gray values over small distances, while low frequency components have little changes in gray values over small distances. (D)</p> Signup and view all the answers

What is the purpose of a low-pass filter in image processing?

<p>To pass over the low frequency components and reduce or eliminate the high frequency components (D)</p> Signup and view all the answers

What is the key property of linear spatial filtering?

<p>It involves convolving an image with a filter kernel (D)</p> Signup and view all the answers

What is the main parameter that determines the degree of blurring in a smoothing filter?

<p>Both the size and values of the kernel coefficients (D)</p> Signup and view all the answers

What is the key property of the box filter kernel?

<p>It has a separable, rectangular coefficient distribution (C)</p> Signup and view all the answers

What is the primary purpose of spatial filtering in image processing?

<p>To modify the image by replacing each pixel value with a function of its neighbors (B)</p> Signup and view all the answers

What is the key difference between a linear spatial filter and a nonlinear spatial filter?

<p>Linear filters use a sum-of-products operation, while nonlinear filters do not (A)</p> Signup and view all the answers

What is another term used to refer to a spatial filter kernel?

<p>Mask, template, or window (B)</p> Signup and view all the answers

What is the mathematical expression for a linear spatial filtering operation?

<p>$g(x, y) = \sum_{i=-1}^{1} \sum_{j=-1}^{1} f(x+i, y+j) w(i, j)$ (C)</p> Signup and view all the answers

What is the purpose of a smoothing (lowpass) spatial filter?

<p>To reduce noise in the image (B)</p> Signup and view all the answers

What is the purpose of a sharpening (highpass) spatial filter?

<p>To enhance the edges in the image (B)</p> Signup and view all the answers

Flashcards are hidden until you start studying

More Like This

Use Quizgecko on...
Browser
Browser