Image Processing Techniques
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Questions and Answers

Which image processing technique is used to redistribute pixel values to adjust image contrast?

  • Contrast Stretching
  • Low-Pass Filtering
  • Histogram Equalization (correct)
  • Gamma Correction

    • What is the purpose of High-Pass Filtering in image processing?

  • To separate objects from the background
  • To adjust image brightness and contrast
  • To enhance image details by emphasizing high-frequency components (correct)
  • To remove noise and smooth the image

    • Which technique is used to remove blur caused by motion or lens distortion?

  • Gamma Correction
  • Deblurring (correct)
  • Contrast Stretching
  • Noise Reduction

    • What is the purpose of Thresholding in image processing?

    <p>To separate objects from the background based on intensity values</p> Signup and view all the answers

    What is the Fourier Transform used for in image processing?

    <p>To decompose an image into frequency components for filtering or compression</p> Signup and view all the answers

    What is the purpose of Image Compression?

    <p>To reduce image size using lossy or lossless algorithms</p> Signup and view all the answers

    Which image processing technique is used to group pixels into regions based on similarity in intensity or texture?

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

    What is the purpose of Image Denoising?

    <p>To remove noise from an image</p> Signup and view all the answers

    Which image processing technique is used to align multiple images of the same scene?

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

    What is the purpose of Median Filtering in image processing?

    <p>To reduce noise by replacing pixel values with the median of neighboring pixels</p> Signup and view all the answers

    Study Notes

    Image Processing Techniques

    Image Enhancement

    • Histogram Equalization: adjusts image contrast by redistributing pixel values
    • Contrast Stretching: increases image contrast by stretching pixel values
    • Gamma Correction: adjusts image brightness and contrast by applying a power-law transformation

    Image Filtering

    • Low-Pass Filtering: removes noise and smooths image by averaging neighboring pixels
    • High-Pass Filtering: enhances image details by emphasizing high-frequency components
    • Median Filtering: reduces noise by replacing pixel values with median of neighboring pixels

    Image Restoration

    • Deblurring: removes blur caused by motion or lens distortion using inverse filtering
    • Noise Reduction: reduces random fluctuations in image intensity using filters or transforms

    Image Segmentation

    • Thresholding: separates objects from background based on intensity values
    • Edge Detection: identifies object boundaries using gradient operators (e.g. Sobel, Canny)
    • Clustering: groups pixels into regions based on similarity in intensity or texture

    Image Transforms

    • Fourier Transform: decomposes image into frequency components for filtering or compression
    • Discrete Cosine Transform (DCT): used in JPEG compression to reduce image size
    • Wavelet Transform: represents image in multiple scales and resolutions for efficient compression

    Other Techniques

    • Image Compression: reduces image size using lossy (e.g. JPEG) or lossless (e.g. PNG) algorithms
    • Image Denoising: removes noise using filters or machine learning-based methods
    • Image Registration: aligns multiple images of the same scene taken at different times or from different viewpoints

    Image Processing Techniques

    Image Enhancement

    • Adjusts image contrast by redistributing pixel values using Histogram Equalization
    • Increases image contrast by stretching pixel values using Contrast Stretching
    • Adjusts image brightness and contrast by applying a power-law transformation using Gamma Correction

    Image Filtering

    • Removes noise and smooths image by averaging neighboring pixels using Low-Pass Filtering
    • Enhances image details by emphasizing high-frequency components using High-Pass Filtering
    • Reduces noise by replacing pixel values with median of neighboring pixels using Median Filtering

    Image Restoration

    • Removes blur caused by motion or lens distortion using Deblurring and inverse filtering
    • Reduces random fluctuations in image intensity using Noise Reduction filters or transforms

    Image Segmentation

    • Separates objects from background based on intensity values using Thresholding
    • Identifies object boundaries using gradient operators (e.g. Sobel, Canny) for Edge Detection
    • Groups pixels into regions based on similarity in intensity or texture using Clustering

    Image Transforms

    • Decomposes image into frequency components for filtering or compression using Fourier Transform
    • Reduces image size using Discrete Cosine Transform (DCT) in JPEG compression
    • Represents image in multiple scales and resolutions using Wavelet Transform for efficient compression

    Other Techniques

    • Reduces image size using Image Compression algorithms (lossy: e.g. JPEG, lossless: e.g. PNG)
    • Removes noise using filters or machine learning-based methods for Image Denoising
    • Aligns multiple images of the same scene taken at different times or from different viewpoints using Image Registration

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    Description

    Learn about various image processing techniques, including image enhancement and filtering methods, to improve image quality and remove noise.

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