3.
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
5.
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
6.
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
8.
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?
10. 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
11.
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
13.
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