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Digital Image Processing: Some Special Techniques Dithering - Duong Anh Duc

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Dithering, also called Halftoning or Color Reduction, is the process of rendering an image on a display device with fewer colors than are in the image. Digital Image Processing: Some Special Techniques Dithering presents about it.

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Nội dung Text: Digital Image Processing: Some Special Techniques Dithering - Duong Anh Duc

  1. Digital Image Processing Some Special Techniques Dithering 21/11/15 Duong Anh Duc - Digital Image Processing 1
  2. Dithering  Dithering, also called Halftoning or Color Reduction, is the process of rendering an image on a display device with fewer colors than are in the image. (Mateus Pins and Hermann Hild)  The number of different colors in an image or on a device is used called its Color Resolution. 21/11/15 Duong Anh Duc - Digital Image Processing 2
  3. Dithering  If the display device has a higher spatial resolution than the image that you are trying to reproduce, it can show a very good image even if its color resolution is less. This is what we will call 'dithering' and is the subject of this work.  Dithering is a one-way operation.  Once an image has been dithered, although it may look like a good reproduction of the original, information is permanently lost.  Many image processing functions fail on dithered images. 21/11/15 Duong Anh Duc - Digital Image Processing 3
  4. Dithering 21/11/15 Duong Anh Duc - Digital Image Processing 4
  5. Dithering Grey-scale and colour simulation  Dithering on a screen or printer is analogous to the half-toning techniques used in the print industry.  A CRT can be considered to be a complex colour “dithering” device with variable colour intensity. 21/11/15 Duong Anh Duc - Digital Image Processing 5
  6. Dithering Grey-scale and colour simulation  We need to display colour and grey-scale images on output devices that have a lower information-carrying capacity.  Cheap printers are bi-level or CMYK - clearly we need to add colours/intensities to approximate an image. 21/11/15 Duong Anh Duc - Digital Image Processing 6
  7. Dithering Methods (Digital Halftoning)  Threshold dithering  Error diffusion  ordered dither dithering  stochastic dither  Floyd-Steinberg  dot diffusion  Burkes  ....  Stucki  Sierra  Jarvis, Judice and Ninke  Stevenson and Arce … 21/11/15 Duong Anh Duc - Digital Image Processing 7
  8. Dithering in Printing Industry  Newspapers  black ink on light paper, rasterization of theimages enables also grey levels, equal pointdensity everywhere, variable size  Color printing  every primary color is rasterized separately,different printing angles ensure unbiased results 21/11/15 Duong Anh Duc - Digital Image Processing 8
  9. Simple shading techniques A series of examples  Original picture, half-toning simulation by a non-PostScript laser printer.  The original image has an 8- bit grey scale palette.  The laser printer has only got a 1-bit palette (ie bi-level, black and white) and must simulate the original shading. 21/11/15 Duong Anh Duc - Digital Image Processing 9
  10. Simple shading techniques An example  Bayer - Ordered Dithering  This method uses a set of regular arrays of values, leading to a regular (and visually poor) output.  This method creates abrupt changes between areas, changes that do not exist on the original. Such artefacts are not desirable. 21/11/15 Duong Anh Duc - Digital Image Processing 10
  11. Simple shading techniques An example  Burkes  This method uses an error- distribution algorithm to minimise percieved errors.  Changes in the average intensity vary quite smoothly, resolution permitting, leading to a more acceptable image. 21/11/15 Duong Anh Duc - Digital Image Processing 11
  12. Simple shading techniques An example  Floyd-Steinberg  FS dithering is popular and commonly used. It is robust and quite general.  FS dithering works best on images with few high- contrast transitions. 21/11/15 Duong Anh Duc - Digital Image Processing 12
  13. Threshold Dithering  every pixel is compared to a threshold t: p t a p>t b t can be:  equal everywhere (e.g. (b–a)/2,arbitrary value, mean value, median, ...)  location dependent (defined locally or globally) 21/11/15 Duong Anh Duc - Digital Image Processing 13
  14. Constant Threshold Dithering sample image threshold values result (values between 0 and 9) corresponds to rounding 21/11/15 Duong Anh Duc - Digital Image Processing 14
  15. Principle of Dithering  Available values a, b  Missing value x between a and b shall besimulated by mixing a-pixels and b-pixels 21/11/15 Duong Anh Duc - Digital Image Processing 15
  16. Principle of Dithering 21/11/15 Duong Anh Duc - Digital Image Processing 16
  17. Dithering a Uniform Area  for a uniform area regular application of this pattern will produce this grey tone interval borders all grey levels in this interval will be mapped to 1/4 21/11/15 Duong Anh Duc - Digital Image Processing 17
  18. Dithering a Uniform Area  This can be done by using a different threshold for every pixel (using the interval borders) 21/11/15 Duong Anh Duc - Digital Image Processing 18
  19. Threshold Matrix  Distances between interval borders are equal, therefore it suffices to define the sequence of the pixel values in the matrix:  instead of only  i.e. for an nxn matrix: values [0,n2–1]  Value k corresponds to threshold value: 2k+1/2n2 21/11/15 Duong Anh Duc - Digital Image Processing 19
  20. Dither Matrix Example dither matrix threshold matrix Value k corresponds to threshold value: 2k+1/2n2 21/11/15 Duong Anh Duc - Digital Image Processing 20
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