Image Dithering.pptx

This presentation demonstrates the Image Dithering and Dithering Methods and Algorithms. It is a good report for the computer science students, especially for students that study image processing subject in computer science department.

1. Image Dithering By: Mohammad Badee Mohammad Tikrit University - Iraq

2. Image Dithering Dithering is the process of reducing the errors that comes from the image quantization technique.

3. Image Dithering It is an image processing operation used to create the illusion of color depth in images with a limited color palette. Dithering also is an intentionally applied form of noise used to randomize quantization error, preventing large-scale patterns such as color banding in images.

4. Image Dithering A common use of dither is converting a grayscale image to black and white, such that the density of black dots in the new image approximates the average gray level in the original.

5. Dithering Methods and Algorithms There are several methods and algorithms that have been designed to perform dithering, these methods are : Thresholding Random dithering Patterning dithers Ordered dithering ( Halftone, Bayer, void-and-cluster ) Error-diffusion

6. Thresholding Dithering It is the simplest method. we simply choose a constant value. All the pixels above that value are considered as 1 and all the value below it are considered as 0.

7. Random Dithering It is the first method and attempt to remedy the drawbacks of thresholding. Each pixel value is compared against a random threshold, resulting in a static image.

8. Patterning Dithering It uses a fixed pattern. For each of the input values, a fixed pattern is placed in the output image. The biggest disadvantage of this technique is that the output image is larger (by a factor of the fixed pattern size) than the input pattern

9. Ordered Dithering ( Halftone, Bayer, void-and-cluster ) It is using a dither matrix. For every pixel in the image, the value of the pattern at the corresponding location is used as a threshold. Neighboring pixels do not affect each other, making this form of dithering suitable for use in animations. Different patterns can generate completely different dithering effects. Though simple to implement, this dithering algorithm is not easily changed to work with free-form, arbitrary palettes.

10. Error-diffusion Dithering Error-diffusion dithering is a feedback process that diffuses the quantization error to neighboring pixels.

11. Error-diffusion Dithering There are several methods and algorithms that have been designed to perform dithering, these methods are : Floyd–Steinberg (FS) dithering Minimized average error dithering by Jarvis, Judice, and Ninke Stucki Dithering Burkes Dithering Sierra Dithering Two-row Sierra Dithering Filter-Sierra Lite Dithering Atkinson Dithering Gradient-based error-diffusion Dithering Lattice-Boltzmann Dithering Electrostatic Halftoning Dithering

12. Thank you.