Today i wrote a program for Histogram Equalization of a Bitmap Image in C.Histogram Equalization simply increases the contrast of images.Basically it balances the overall contrast of image.There is three basic steps in this program:First of all we should calculate probability distribution function of each pixel intensity,then we should calculate Cumulative Distribution function (CDF) of these intensity.Then we will calculate the equalized value on that intensity.
Here is the input & output image for the histogram equalization:-
We have to be consider on some more topics on Histogram Equalization like:-
1)Disadvantages of He
2)When we should avoid He?
3)How can we overcome demerits of He?
4)Real world Application of He.
1)Disadvantage of He:-Followings are some disadvantages of He-
a)It reduces the brightness of some high contrast images.
b)If there are gray values which are physically far apart from each other in the image then this method fails.
c)This method is indiscriminate.It may increase the contrast of background noise & decrease the usable
signal.
d)Histogram equalization often produces unrealistic effects in photographs.
e) It produces undesirable undesirable effects when applied low color depth image.
2)When we would emphasize on local contrast rather than overall contrast then we should avoid Histogram Equalization.
3)We can overcome demerit of He using other generalized form of this like Adaptive histogram equalization (AHE) or Contrast limited adaptive histogram equalization(CLAHE).There are focus on local contrasts rather than overall contrast .they computes several histogram for this.
4)Here some real world application of He-:
a)It is very useful in scientific images like X-ray,thermal,Satellite.
b)It is also used in Biological Neural Network so as to maximize output firing rate of neuron .
 |
| Input Color Image |
 |
| Equalized Image |
We have to be consider on some more topics on Histogram Equalization like:-
1)Disadvantages of He
2)When we should avoid He?
3)How can we overcome demerits of He?
4)Real world Application of He.
1)Disadvantage of He:-Followings are some disadvantages of He-
a)It reduces the brightness of some high contrast images.
b)If there are gray values which are physically far apart from each other in the image then this method fails.
c)This method is indiscriminate.It may increase the contrast of background noise & decrease the usable
signal.
d)Histogram equalization often produces unrealistic effects in photographs.
e) It produces undesirable undesirable effects when applied low color depth image.
2)When we would emphasize on local contrast rather than overall contrast then we should avoid Histogram Equalization.
3)We can overcome demerit of He using other generalized form of this like Adaptive histogram equalization (AHE) or Contrast limited adaptive histogram equalization(CLAHE).There are focus on local contrasts rather than overall contrast .they computes several histogram for this.
4)Here some real world application of He-:
a)It is very useful in scientific images like X-ray,thermal,Satellite.
b)It is also used in Biological Neural Network so as to maximize output firing rate of neuron .
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