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Basic_image_processing

Sampling and Quantization

Exploring fundamental techniques in image processing to modify and analyze pixel values.

  • Sampling Even Pixels: Sampling image pixels at even positions.
  • Downsampling: Reducing the image size by a factor of 2.
  • Upsampling: Restoring the downsampled image from step 2 back to its original size.
  • Quantization: Reducing the image from 256 gray levels to 8 levels.

Blur and Edge Detection

Applying various filters and techniques to blur images and detect edges.

  • Average Filter Blur: Blurring the image using an average filter.
  • Gaussian Filter Blur: Applying a Gaussian filter for image blurring.
  • Median Filter Blur: Using a median filter for image blurring.
  • Sobel/Laplacian Edge Detection: Finding edges using Sobel or Laplacian operators.
  • Canny Edge Detection: Edge detection using the Canny algorithm.

Huffman Coding

Implementing Huffman data compression for efficient data representation.

Morphology

Manipulating image structures using morphological operations.

  • Binary Image Conversion: Converting the image into a binary format.
  • Dilation and Erosion: Applying dilation and erosion with a 3x3 structural element.
  • Opening and Closing: Performing opening and closing operations based on dilation and erosion.
  • Edge Detection: Finding edges using methods from steps 1 to 3.

Each section provides a practical approach to basic image processing techniques, offering a foundation for further exploration in this field.

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