69 lines
3.7 KiB
Markdown
69 lines
3.7 KiB
Markdown
|
# Histogram Equalization
|
||
|
|
|
||
|
|
Histogram equalization capabilities in GIL are demonstrated by the program `histogram_equalization`, compiled from the sources `example/histogram_equalization.cpp`.
|
||
|
|
|
||
|
|
## Synopsis
|
||
|
|
|
||
|
|
`histogram_equalization`
|
||
|
|
|
||
|
|
The program doesn't take any argument on the command line.
|
||
|
|
|
||
|
|
Hough line transform solves the equation of a line in reverse, but in *polar coordinates*! The implementation will make each pixel vote on all possible lines it could be part of, limited by input Hough parameters.
|
||
|
|
|
||
|
|
A line in polar coordinates is represented by normal to it in polar coordinates, as shown in example here
|
||
|
|
https://docs.opencv.org/3.4/d9/db0/tutorial_hough_lines.html
|
||
|
|
|
||
|
|
Since real line is the diagonal throughout the image, the angle of normal to it will 45 degrees. (1s represent real line, 5s represent normal to it).
|
||
|
|
|
||
|
|
```
|
||
|
|
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
|
||
|
|
0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
|
||
|
|
0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
|
||
|
|
0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
|
||
|
|
0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
|
||
|
|
0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
|
||
|
|
5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
|
||
|
|
```
|
||
|
|
|
||
|
|
It is obvious that the angle for the expected Hough transform is 45 degrees (angle between 5s and bottom 0s). Now we
|
||
|
|
need to find the length of 5s. Since 5s, 1s and bottom 0s form a right triangle, we know that bottom 0s are 32 in length
|
||
|
|
and is a hypotenuse! Using trivial trigonometry we know that the length we are searching for is 32 * cos(45).
|
||
|
|
|
||
|
|
`histogram_equalization` expects to find an image called `test_adaptive.png` in the current directory, and produces an image in return, where the equalization have been applied: `histogram_gray_equalized.png`.
|
||
|
|
|
||
|
|
## Specific requirements
|
||
|
|
|
||
|
|
### Build requirements
|
||
|
|
|
||
|
|
- A C++ compiler compliant with C++14 or above
|
||
|
|
- The PNG library installed and configured.
|
||
|
|
|
||
|
|
### Execution requirements
|
||
|
|
|
||
|
|
- `histogram_equalization` expects to find an image called `test_adaptive.png` in the current directory.
|