Basics of Image Factors Quiz

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Questions and Answers

What does the Bidirectional Reflectance Distribution Function (BRDF) model describe?

  • How bright a surface appears when viewed from one direction when light falls on it from another (correct)
  • The color of the light source hitting a surface
  • The transparency properties of a surface
  • How light is absorbed by a surface

Which law states that the amount of light reflected from a surface is proportional to cos(θ), where θ is the angle of illumination?

  • Fermat's principle
  • Huygens' principle
  • Snell's law
  • Lambert's cosine law (correct)

What do demosaicing algorithms do in the context of image processing?

  • Enhance the sharpness of images
  • Estimate missing color values for pixels based on surrounding pixel colors (correct)
  • Apply distortion corrections to images
  • Adjust the contrast of images

In Bayer arrangement of color filters on a camera sensor, what percentage of the filter pattern is green?

<p>50% (B)</p> Signup and view all the answers

What does the albedo (ρ) of a surface represent?

<p>Amount of light absorbed by the surface (C)</p> Signup and view all the answers

Which component of light arriving at a sensor involves the color of the light source and the color of the surface being captured?

<p>Sensor Filter pattern (C)</p> Signup and view all the answers

What does the digitalization of an image involve?

<p>Converting it into a series of numbers and storing them in a computer storage system. (B)</p> Signup and view all the answers

How are pixels represented in an image?

<p>As dots arranged in rows and columns, each with a specific color. (C)</p> Signup and view all the answers

What numerical values are used to determine the colors of pixels in an image?

<p>Assigned numerical values based on the RGB model. (B)</p> Signup and view all the answers

What does the tuple (0,0,0) represent in the RGB model for pixel colors?

<p>Black color. (D)</p> Signup and view all the answers

In the RGB model, what does each pixel have as components?

<p>(value for red component, value for green component, value for blue component) (C)</p> Signup and view all the answers

What is the main concept behind Linearity or Superposition principle in image processing?

<p>The output images after applying individual filters will be the same regardless of the order they are applied. (B)</p> Signup and view all the answers

What is the purpose of blurring in image processing?

<p>To average pixel values within a neighborhood and make sharp edges smoother. (C)</p> Signup and view all the answers

Why are large kernels preferred for blurring in image processing?

<p>To achieve a greater smoothening effect by producing larger averaging values. (D)</p> Signup and view all the answers

Which technique is commonly used for noise reduction in image preprocessing?

<p>Median blur (A)</p> Signup and view all the answers

What is the effect of blurring often referred to as?

<p>'Low pass filter' effect (B)</p> Signup and view all the answers

What do steps involved in blurring an image include?

<p>Multiplying each value of the kernel with the corresponding value of the image matrix. (C)</p> Signup and view all the answers

What is the purpose of the kernel H(u,v) in image processing?

<p>To detect edges in an image (D)</p> Signup and view all the answers

In the context of convolution, what is the process of applying a linear filter to an image?

<p>Centering a kernel on a pixel and summing the results (D)</p> Signup and view all the answers

Why is it important that correlation and convolution are Linear Shift-Invariant operators in computer vision?

<p>To ensure that shifting a signal commutes with applying the operator (A)</p> Signup and view all the answers

How does convolution differ from correlation when applying operators in computer vision?

<p>Correlation flips the filter in both directions, while convolution doesn't (A)</p> Signup and view all the answers

What is the primary reason for using kernels in image processing?

<p>To apply different filters for feature extraction (D)</p> Signup and view all the answers

How does convolution help in detecting edges in images?

<p>By summing multiplied pixel values under a kernel to highlight intensity changes (A)</p> Signup and view all the answers

What is the purpose of histogram equalization on images?

<p>To stretch the histogram of the image for higher contrast (D)</p> Signup and view all the answers

How does histogram equalization impact the image histogram?

<p>It makes the histogram flatter (C)</p> Signup and view all the answers

For a grey-scale image, what does each pixel represent?

<p>Brightness or intensity value (D)</p> Signup and view all the answers

What does each channel of an RGB-formatted color image represent?

<p>Intensity value of a specific color (C)</p> Signup and view all the answers

How are cumulative distribution values calculated in histogram equalization?

<p>By summing up intensity values for each pixel (D)</p> Signup and view all the answers

What happens to the bars of a histogram after applying histogram equalization?

<p>Bars extend to both ends of the spectrum (B)</p> Signup and view all the answers

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