Chapter 5: Specialized image processing

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This chapter describes different specialized image processing techniques.

• Specialized image processing in general
• Rearranging areas in your grabbed image
• Deinterlacing
• • Discard algorithm on the entire image
  • Averaging algorithm on the entire image
  • Bob algorithm on the entire image
  • Adaptive algorithms
• Correcting dead pixels
• Removing CCD artifacts from grabbed images
• • How to perform a flat-field correction
  • Electrical bias (offset image or constant)
  • Thermal agitation (dark image or constant)
  • CCD sensitivity (flat image or constant)
  • Gain
• Transform and denoise images using wavelets
• • Wavelet context
  • • Filters
    • Operation mode
  • Wavelet transformations
  • • Results and drawings
  • Wavelet denoising
• Co-occurrence matrix statistics
• • Building the grayscale co-occurrence matrix
  • Tiling your image
  • Supported co-occurrence statistics
  • A co-occurrence example
  • Limiting the bit depth of your image
• Fast Fourier Transform
• • Magnitude and phase
  • Filtering an image
• Discrete Cosine Transform
• Peak intensity detection and depth maps
• • Setting up peak intensity detection
  • Generating an uncorrected depth map
  • Multiple peaks in a single lane
  • Extraction of peaks from a multi-frame buffer
• Augmentation
• • Steps to augment an image
  • Priority
  • Probability
  • Randomness and seeds