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Psuedo color

The document discusses pseudo color images and techniques for converting grayscale images to color. It defines pseudo color images as grayscale images mapped to color according to a lookup table or function. It describes various color schemes for this mapping, including grayscale schemes that use shades of gray and oscillating schemes that emphasize certain grayscale ranges in color. The document also discusses using piecewise linear functions and smooth non-linear functions to transform grayscale levels to color for purposes such as enhancing contrast or reducing noise in images.

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Maria Shoukat IUB.edu.pk(RYK)
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 A pseudo color image (sometimes styled pseudo- color or pseudo color) is derived from a gray scale image by mapping each intensity value to a color according to a table or function. Definition
  Define vs Picture: Defined it!
 Color Schemes  A color scheme is a pseudo color lookup table. Like a true color lookup table, it converts file values (in this case, class values) to output brightness values. In pseudo color, though, the color for each input file value is controlled separately and distinctly. You can explicitly assign colors to each class value in the layer that is displayed. Schemes
 Gray Scale Color Scheme  A gray scale color scheme is a pseudo color lookup table that is composed completely of shades of gray. When a gray scale color scheme is applied automatically, it generally consists of a gradation ranging from black to white. This is also called a gray level slice.  A gray scale color scheme for categorical data should not be confused with gray scale mapping of continuous data. Schemes
 Pseudo Image Processing gray level to color transformation
  The Pseudo Color module colonizes the image based on its grays cale value which maps to a full RGB color range. Pseudo Color images can help to reveal image qualities that would not be readily visible within the image's true color.  The false color of a pixel is created by determined by summing its RGB values and mapping them into a 768 row lookup table. This lookup table is created by oscillating through the RGB color table from Blue to Red to create 768 unique colors. How it work?
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 Change the phase and frequency of each sinusoid can emphasize (in color) ranges in the gray scale.  Peak → constant color region.  Valley →rapid changed color region  A small change in the phase between the three transforms produces little change in pixels whose gray level corresponding to the peaks in the sinusoidal.  Pixels with gray level values in the steep section of the sinusoids are assigned much strong color. Gray-level to color transformation
  Image enhancement techniques have been widely used in many applications of image processing where the subjective quality of images is important for human interpretation. Contrast is an important factor in any subjective evaluation of image quality.  contrast is the difference in visual properties that makes an object distinguishable from other objects and the background. Piecewise linear function
 Piecewise linear function
  These algorithms are applied in order to reduce noise and/or to prepare images for further processing such as segmentation. We distinguish between linear and non- linear algorithms where the former are amenable to analysis in the Fourier domain and the latter are not. Smooth non-linear function
  Difference: Smooth non-linear function
Psuedo color