Digital Image Fundamentals Quiz

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Questions and Answers

What are the fundamental steps in image processing?

Image acquisition, Sampling and quantization, Image representation, Image recognition

What are the basic relationships between pixels in image processing?

Neighbor's connectivity

What are the two color image models mentioned in the text?

RGB and CMY

What are the spatial domain image processing methods discussed?

<p>Image Negative, Log, Power Law, Image Smoothening, Image Sharpening</p> Signup and view all the answers

What are the different types of image compression mentioned?

<p>Error free compression and Lossy compression</p> Signup and view all the answers

Study Notes

Image Processing Fundamentals

  • The fundamental steps in image processing are: image acquisition, image enhancement, image restoration, image compression, and image reconstruction.

Pixel Relationships

  • Pixels are the basic units of a digital image, and each pixel has a specific value (intensity) which determines its brightness.
  • Pixels are arranged in a 2D grid, with each pixel having a horizontal and vertical coordinate (x, y).
  • The relationships between pixels are based on their spatial positioning, with neighboring pixels being those that are directly adjacent (horizontally, vertically, or diagonally) to a given pixel.

Color Image Models

  • RGB (Red, Green, Blue) color model is an additive model, where the combination of red, green, and blue light produces the final color.
  • CMYK (Cyan, Magenta, Yellow, Black) color model is a subtractive model, where the combination of cyan, magenta, and yellow inks absorbs certain wavelengths of light to produce the final color.

Spatial Domain Image Processing

  • Spatial domain image processing methods operate directly on the pixels of the image, without transforming the image into another domain (e.g. frequency domain).
  • Spatial domain methods discussed include: image negation, logarithmic transformation, and power-law transformation.

Image Compression

  • Lossless compression: reduces the size of the image without losing any of the original data (e.g. Huffman coding, LZW coding).
  • Lossy compression: reduces the size of the image by discarding some of the original data (e.g. JPEG compression).

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