Image Processing Techniques Quiz
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Questions and Answers

What is the main difference between bilinear and bicubic interpolation?

  • Bilinear is faster but produces more artifacts
  • Bilinear uses 4 neighbors, while bicubic uses 16 (correct)
  • Bilinear uses 16 neighbors, while bicubic uses 4
  • Bicubic produces less detailed images than bilinear

    • Which method reduces noise in noisy images by averaging multiple images?

  • Image registration
  • Image subtraction
  • Image addition (correct)
  • Image compression

    • How is the electromagnetic spectrum typically expressed?

  • Pixel and amplitude
  • Wavelength, frequency, and energy (correct)
  • Speed and intensity
  • Frequency and time

    • How is a grayscale image typically stored?

    <p>Using 8-bit resolution with 256 gray levels</p> Signup and view all the answers

    What term describes the process of aligning two or more images before applying image arithmetic operations?

    <p>Image registration</p> Signup and view all the answers

    What happens when you reduce the spatial resolution of an image?

    <p>The image size decreases and quality degrades</p> Signup and view all the answers

    Which technique is used to guess the intensity values at missing locations in an image?

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

    What is the effect of adding a constant to each pixel's grayscale value?

    <p>Increases brightness</p> Signup and view all the answers

    What is the primary purpose of gray-level slicing in image processing?

    <p>Highlighting specific gray levels in an image</p> Signup and view all the answers

    Which transformation is correctly associated with gamma correction?

    <p>Power-law transformation</p> Signup and view all the answers

    Why might the Canny edge detection algorithm be preferred over basic gradient methods?

    <p>It applies edge linking to better differentiate between edges and texture</p> Signup and view all the answers

    What major disadvantage does the Hough Transform encounter when detecting lines in images?

    <p>It has high memory consumption</p> Signup and view all the answers

    In geometric primitive extraction, what defines an outlier?

    <p>A point that does not conform to the expected model</p> Signup and view all the answers

    What defines the spatial resolution of a digital image?

    <p>The number of pixels in the image</p> Signup and view all the answers

    What is the purpose of bit-plane slicing?

    <p>To isolate specific bits contributing to the image</p> Signup and view all the answers

    Which interpolation method typically uses 16 nearest neighbors?

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

    What does histogram equalization aim to achieve?

    <p>A uniform distribution of pixel values</p> Signup and view all the answers

    What type of transformation function is both complex and requires user input?

    <p>Piecewise-linear transformation</p> Signup and view all the answers

    Which operation is used to reverse pixel intensities in an image?

    <p>Image negatives</p> Signup and view all the answers

    In spatial filtering, what is a filter mask also known as?

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

    Which technique is used for image sharpening through spatial differentiation?

    <p>Laplacian filter</p> Signup and view all the answers

    What is the typical bit-depth used for grayscale images?

    <p>8 bits</p> Signup and view all the answers

    Which of the following is a true statement regarding linear filtering?

    <p>The operation performed on image pixels is linear</p> Signup and view all the answers

    What is the common property of order-statistic filters?

    <p>They function as non-linear spatial filters</p> Signup and view all the answers

    Which operation is not a form of point operation?

    <p>Histogram equalization</p> Signup and view all the answers

    What does the term 'quantization' specifically refer to in digital imaging?

    <p>Digitizing amplitude values</p> Signup and view all the answers

    How do frequency domain filters compare to spatial domain filters?

    <p>They are more sophisticated</p> Signup and view all the answers

    What is a common use of contrast stretching in image processing?

    <p>To enhance the dynamic range of gray levels</p> Signup and view all the answers

    What is the primary benefit of hysteresis thresholding in the Canny edge detector?

    <p>Connect edge pixels</p> Signup and view all the answers

    Which step is first in the general procedure for applying gradient operators?

    <p>Smoothing the image</p> Signup and view all the answers

    What is indicated by zero-crossing in the Marr-Hildreth method?

    <p>Location of an edge</p> Signup and view all the answers

    What is a key advantage of using the Hough Transform for line detection?

    <p>It is robust against noise and occlusions</p> Signup and view all the answers

    In RANSAC, what defines inliers?

    <p>Points that fit well with the hypothesized model</p> Signup and view all the answers

    What factor is unique to the Hough Transform when detecting circles compared to lines?

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

    What is the purpose of geometric primitive extraction in image processing?

    <p>To create higher-level geometric shapes</p> Signup and view all the answers

    Which transformation is linked closely with gamma correction?

    <p>Power-law transformation</p> Signup and view all the answers

    What does the equation $s = L - 1 - r$ represent?

    <p>Image negative transformation</p> Signup and view all the answers

    What is a common disadvantage of the Hough Transform when detecting lines?

    <p>High memory consumption</p> Signup and view all the answers

    How many points are needed to define a line in the RANSAC algorithm?

    <p>2</p> Signup and view all the answers

    Which method is specifically employed for circle detection in images?

    <p>Hough Transform</p> Signup and view all the answers

    What is the output of applying the Hough Transform for line detection?

    <p>Set of line equations</p> Signup and view all the answers

    What does contrast stretching affect regarding an image?

    <p>Dynamic range of gray levels</p> Signup and view all the answers

    What type of noise is most effectively reduced by using a median filter?

    <p>Salt-and-pepper noise</p> Signup and view all the answers

    What is the purpose of using smoothing filters in image processing?

    <p>Noise reduction</p> Signup and view all the answers

    In image processing, how does convolution differ from correlation?

    <p>Convolution rotates the filter mask by 180 degrees</p> Signup and view all the answers

    What is the role of hysteresis thresholding in edge detection?

    <p>To connect edges through weak gradients</p> Signup and view all the answers

    What does the Laplacian of Gaussian (LoG) method accomplish in edge detection?

    <p>Finds zero-crossings after smoothing</p> Signup and view all the answers

    Which filter is known for being effective in detecting edges in images with significant texture?

    <p>Canny filter</p> Signup and view all the answers

    What is the primary use of the Sobel operator in image processing?

    <p>To estimate image gradients</p> Signup and view all the answers

    In the context of the Marr-Hildreth algorithm, what typically follows Gaussian smoothing?

    <p>Applying Laplacian</p> Signup and view all the answers

    What best describes how edge detection generates continuous curves?

    <p>By linking adjacent high contrast regions</p> Signup and view all the answers

    What happens when the Gaussian kernel size is increased in the Canny edge detection algorithm?

    <p>Detects fewer edges in the image</p> Signup and view all the answers

    Which method of edge detection employs gradient information to identify edges?

    <p>Sobel filter</p> Signup and view all the answers

    What is the primary effect of using a Laplacian filter with a negative center value?

    <p>Produces grayish edge lines on a dark background</p> Signup and view all the answers

    What is the consequence of applying the Canny algorithm to images with significant noise?

    <p>It may miss edges due to noise sensitivity</p> Signup and view all the answers

    Study Notes

    Image Processing Techniques

    • Interpolation: Techniques for estimating pixel values at missing locations in image.

    • Nearest Neighbor: Simplest, uses nearest pixel.

    • Bilinear: Uses 4 nearest neighbors.

    • Bicubic: Uses 16 nearest neighbors.

    • Image Arithmetic:

    • Image addition: Averages multiple noisy images, reducing noise.

    • Electromagnetic Spectrum: Typically represented by wavelength, frequency, and energy.

    • Grayscale Images: Usually stored using 8-bit resolution with 256 gray levels.

    • Image Registration: Aligning two or more images.

    • Spatial Resolution Reduction: Decreases image size and quality.

    • Brightness Increase: Adding a constant to each pixel's grayscale value.

    Distance Measures

    • D8 distance (Chessboard distance): A measure of distance between pixels in an image.

    Image Representations

    • RGB Images: Composed of Red, Green, and Blue channels.
    • Digital Images: 2-dimensional functions with discrete pixel values.
    • Intensity at a Pixel: The amplitude of light at a specific point in the image
    • Connected Components: A set of connected pixels.

    Image Enhancement Techniques

    • Histogram Equalization: Aims to create a uniform distribution of pixel values.
    • Histogram Matching: Matches the histogram of an image to a specified shape.
    • Bit-Plane Slicing: Isolates the contribution of specific bits to the image.
    • Contrast Stretching: Increases the dynamic range of gray levels.

    Point Operations

    • Image Negatives: Reverses pixel intensities.
    • Log Transformations: s=c⋅log⁡(1+r), where s is the output value, r is the input value, and c and γ are constants.
    • Power-Law Transformations: s=c⋅rγ, where s is the output value, r is the input value, and c and γ are constants.

    Spatial Filtering

    • Linear Filters (Smoothing Filters): Lowpass filters; reduce noise, blur edges.
    • Averaging Filters: Blurs edges in an image.
    • Median Filters: Non-linear, effective against salt-and-pepper noise (impulse noise).
    • Laplacian Filters: Enhance edges and produce double edges.
    • Highpass Filters: Enhance edges and fine details.
    • Gradient Filters: Highlight edges by computing the gradient.
    • Sobel, Prewitt: Estimate gradients using orthogonal masks.
    • Kernel (Filter Mask): A filter mask in spatial filtering.
    • Convolution vs. Correlation: Convolution rotates the filter mask by 180 degrees; correlation doesn't.
    • Unsharp Masking: Subtracting a blurred image from the original to sharpen image details.

    Edge Detection

    • Marr-Hildreth (LoG): Detects edges as zero-crossings after Gaussian smoothing.
    • Canny Edge Detector: Multi-step procedure with hysteresis thresholding, non-maximum suppression.
    • Sobel and Prewitt: Gradient-based edge detection methods.
    • Hysteresis Thresholding: Links edge pixels based on high and low thresholds.
    • Zero-crossing: Marks the location of an edge (Marr-Hildreth).
    • Causes of Edges: Depth discontinuities (e.g., object boundaries)

    Geometric Primitive Extraction

    • Hough Transform: Detects lines, circles, etc, in a parameter space.
    • Detects lines and circles with high robustness to noise.
    • High memory consumption, less computationally efficient.
    • RANSAC (Random Sample Consensus): Robust method for fitting models (lines, circles, planes) despite outliers.
    • Addresses outliers by randomly sampling data points.
    • Can handle a moderate amount of outliers.
    • Requires random sampling.
    • Inliers and Outliers: Inliers fit the model, outliers don't.

    Types of Noise and Processing

    • Salt-and-pepper noise: Noise in digital images characterized by isolated pixels with very high or very low intensity values.
    • Gaussian noise: Noise in images that is considered to be a Gaussian error (random variable).

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    Description

    Test your knowledge of various image processing techniques, including interpolation methods, noise reduction, and image alignment. This quiz covers fundamental concepts essential for understanding how digital images are manipulated and enhanced in different applications.

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