Lecture3.pptx
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This document discusses various point operations that can be performed on digital images. Point operations modify pixel values without considering neighboring pixels. The key point operations covered are arithmetic operations like addition/subtraction and multiplication/division, color operations like changing lighting color and swapping/eliminating channels, multiple image operations like combining two images, and histograms which show pixel value distributions. Point operations are useful for image pre-processing tasks like contrast adjustment and color corrections.
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Lecture3.pptx
- 1. LECTURE 3 Digital Image Processing
- 3. Content Point Processing 2.1 Introduction …………………………….……………………. 2.2 Arithmetic operations……………………………………… 2.3 Color operations………………..………………………….... 2.4 Multiple image operations……………………………….. 2.5 Histograms ……………………………….…………………… 2.6 Lookup tables………………………………………………...
- 4. Introduction Neighborhood processing vs. Point operations
- 5. Introduction Although point operations are the simplest, they contain some of the most powerful and widely used of all image processing operations. They are especially useful in image pre-processing, where an image is required to be modified before the main job is attempted
- 6. Arithmetic operations These operations act by applying a simple function y = f(x) Types of operations: 1. Addition/Subtraction 2. Multiplications/Division 3. Complementary
- 7. Addition/Subtraction To add /subtract a constant from each pixel in the image. y = x ± C
- 9. Multiplications/Division To multiply /divide each pixel in the image x in/by a constant c.
- 11. Complementary The complement of a grey scale image is its photographic negative.
- 12. Complementary
- 13. Image Solarization Complementing only part of the image.
- 14. Image Solarization The image recorded on a negative or on a print is wholly or partially reversed in tone. Dark areas appear light or light areas appear dark.
- 16. Color Images Operations Possible channel operations: Changing the image lighting color. Swapping image channels. Eliminating color channels
- 17. Changing the image lighting color To change the intensity of one or more channel by adding or subtracting a constant R + C => the image will be reddish G + C => the image will be greenish B + C => the image will be bluish R,G + C => the image will be yellowish
- 18. Changing the image lighting color
- 19. Swapping image channels To exchange the intensity between the image channels. R , G => the image will be GRB G , B => the image will be RBG B , R => the image will be BGR Other spaces could be obtained by swapping 2 channels at once like; GBR and BRG.
- 21. Eliminating color channels To set one or more color channels by zero values. Eliminating R => image will be in cyan Eliminating G => image will be in magenta Eliminating B => image will be in yellow Eliminating R,G => image will be in blue Eliminating G,B => image will be in red Eliminating B,R => image will be in green
- 23. Multiple Image Operations Perform operations between two images or more for: 1. Enhance the image visual appeal. 2. Getting specific part of image between similar images.(eg. motion tracking) 3. For some preprocessing purposes.
- 24. Multiple Image Operations Assume two images x1 and x2: the possible operations between x1 and x2:
- 25. Example
- 27. Image Histogram It is a graph indicating the number of times each grey level occurs in the image.
- 30. Why Histogram? To know image features: Most color(intensity) in the image Image Contrast Image Brightness For segmentation purpose A threshold can be used to segment the image into parts.
- 31. Histogram Image features In a dark image, the grey levels would be clustered at the lower end. In a uniformly bright image, the grey levels would be clustered at the upper end. In a well contrasted image, the grey levels would be well spread out over much of the range.