Image Representation and HDR Quiz
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Questions and Answers

What happens to the iso-preference curves as the values for N and k increase?

  • The curves remain constant.
  • The curves become horizontal.
  • The curves shift right and upward. (correct)
  • The curves shift left and downward.
  • Which interpolation technique creates a chessboard effect due to pixel replication?

  • Bilinear interpolation
  • Cubic interpolation
  • Nearest neighbor interpolation (correct)
  • Higher-order non-linear interpolation
  • How can an image be reduced in size when it is too large to fit on the screen?

  • By zooming in on the image.
  • By generating a half-sized version. (correct)
  • By increasing the pixel resolution.
  • By applying bilinear interpolation only.
  • What does a vertical shift in the iso-preference curves suggest about images with high detail?

    <p>Fewer intensity levels are required.</p> Signup and view all the answers

    Which of the following interpolation methods utilizes four nearest neighbors to determine new pixel values?

    <p>Bilinear interpolation</p> Signup and view all the answers

    What does a high dynamic range image represent?

    <p>High contrast image</p> Signup and view all the answers

    If an image is represented by $N = 2048$ and $k = 8$, how many bytes does it occupy?

    <p>12 M bytes</p> Signup and view all the answers

    How is a binary image defined?

    <p>Only two values for a pixel: 0 or 1</p> Signup and view all the answers

    What is the total number of colors that can be represented in the RGB color model?

    <p>16,777,216</p> Signup and view all the answers

    Which of the following statements about spatial resolution is true?

    <p>It is the smallest discernible detail in an image</p> Signup and view all the answers

    What does gray-level resolution indicate?

    <p>The smallest change in intensity levels discernible by a viewer</p> Signup and view all the answers

    How many gray levels are available in a gray-level image represented by 1 byte?

    <p>256 levels</p> Signup and view all the answers

    What is the relationship between spatial resolution and image size?

    <p>They represent completely different concepts</p> Signup and view all the answers

    What are the two primary stages in the digitization process of images?

    <p>Sampling and quantization</p> Signup and view all the answers

    In the equation $L = 2^k$, what does 'L' represent?

    <p>Gray-level resolution</p> Signup and view all the answers

    What does the dynamic range of an image refer to?

    <p>The range of values spanned by the gray scale</p> Signup and view all the answers

    What does the spatial resolution of an image refer to?

    <p>The detail an image holds, defined by rows (M) and columns (N)</p> Signup and view all the answers

    Which representation method is NOT commonly used for digital images?

    <p>A physical sculpture of the image</p> Signup and view all the answers

    If an image has 8 bits for gray-level quantization, what is the gray-level resolution?

    <p>256</p> Signup and view all the answers

    What happens during the image sampling process?

    <p>Assigning numeric values to points on the sensor array</p> Signup and view all the answers

    Which of the following is true about quantization in image processing?

    <p>It maps continuous amplitude values to discrete levels.</p> Signup and view all the answers

    Study Notes

    High Dynamic Range

    • High dynamic range (HDR) refers to a higher contrast image, meaning the difference between the darkest and lightest areas of the image is greater.

    Image Storage Requirements

    • The number of bits required to store an image is calculated using the formula: b (bit)= 𝑀 × 𝑁 × 𝑘 or b (bit)= 𝑁 2 × 𝑘
    • 𝑀 represents the number of rows, 𝑁 represents the number of columns, and 𝑘 represents the number of bits per pixel.
    • Example image sizes:
      • 𝑁=256, 𝑘=8: 65536 bytes
      • 𝑁=2048, 𝑘=8: 12 M bytes
      • 𝑁=8192, 𝑘=8: 192 M bytes

    Image Representation

    • Binary Image:

      • Represents pixels with only two values (0 or 1) using 1 bit.
      • A 256×256 binary image file is 65,536 bits or 8,192 bytes.
    • Grey-Level Image:

      • Represents pixel values using 1 byte (28), ranging from 0 to 255, representing black to white with 256 grey levels.
      • A 256×256 grey-level image file is 65,536 bytes.
    • Color Images:

      • RGB Model: Utilizes Red, Green, and Blue primaries to represent color.
      • Number of Representable Colors: (28)3 = 224 = 16,777,216 (true color)
      • Examples:
        • (0, 255, 0): Green
        • (255, 0, 0): Red
        • (0, 120, 0): Light Green
        • (100, 100, 0): Yellow

    Spatial and Intensity Resolution

    • Spatial Resolution: The smallest discernible detail in an image, measured as dots (pixels) per unit distance.
      • Related to image size but not the same.
    • Grey-Level Resolution: The smallest discernible change in intensity level.
      • Measured in the number of grey levels used (e.g., 256 levels, 128 levels, etc.)

    Empirical Study of Resolutions

    • Goal: To determine the impact of 𝑘 (bits per pixel) and 𝑁 (image size) on image quality.
    • Iso-Preference Curves:
      • Larger values of 𝑁 and 𝑘 generally lead to better picture quality.
      • Curves tend to become vertical as the detail in the image increases, indicating that for high-detail images fewer intensity levels are required.

    Zooming and Shrinking Digital Images

    • Zooming: Increasing the size of an image.
      • Methods:
        • Nearest Neighbor Interpolation: Replicating pixels, resulting in a chessboard effect.
        • Bilinear Interpolation: Using four nearest neighbors for interpolation.
        • Higher-Order Non-linear Interpolation: Using more neighbors for interpolation.
    • Shrinking: Reducing the size of an image.
      • Used to resize large images for display on smaller screens.

    Image Sampling and Quantization

    • Digitization Process: Converts continuous data 𝑓(𝑥, 𝑦) into a digital image.
      • Sampling: Digitizing coordinate values (determining 𝑀 and 𝑁).
      • Quantization: Digitizing amplitude values (determining gray-level resolution 𝐿, where 𝐿 = 2𝑘).
    • Dynamic Range: The range of values spanned by the gray scale, from 𝐿𝑚𝑖𝑛 to 𝐿𝑚𝑎𝑥.

    Representing Digital Images

    • Digital images can be represented in three ways:
      • A 2.5D Plot: Visualizes the function as a topography.
      • An Image on a Monitor: Allows for visual representation of the image.
      • Printing Numerical Values in an Array: Useful for implementation in algorithms.

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    Description

    Test your knowledge on High Dynamic Range (HDR) imaging and image storage requirements. This quiz covers binary, grey-level, and color image representations, along with calculations for image size based on pixel values. Enhance your understanding of digital images and their storage needs.

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