Possible Duplicate:
How is Weighted Thresholded Histogram Equalization different from Gamma Correction Image enhancement

In case of Weighted Thresholded Histogram Equalization we use:-

calculate, the Weighted Probablity Density Function for Image using,

Pwt(k) = ((P(k)-Pl)/(Pu-Pl))^r* Pu,

Where Pu is the highest probablity of a intensity in a Image. Pl is the lowest probablity of a intensity in a Image. P(k) is the Probablity Density Function for the Image,ie the no of pixels having the intensity k in a image.

then perform Histogram Equalization on the image using, calculating Cumulative Distribution Function

Cwt(k) = m=0∑k Pwt(m);
Im(i,j) = Wout*Cwt(F(i,j));

For r<1 the Power Law Transformation function will give a higher weight to the low probablities in the PDF than the high probablities.

How is this procedure conceptually different from the Gamma Correction technique , explain if similiar how much similiarity is there or if something is different , Explain where does it deviate from Gamma Correction method for Single Image Enhancement.

Does this Procedure Passes for Being Called as Gamma Correction in some Aspect OR Do some Changes are Required.

  • $\begingroup$ Have you read about Gamma Correction, e.g. this link on Wikipedia: en.wikipedia.org/wiki/Gamma_correction? It's really quite simple compared to histogram equalization. $\endgroup$ – Mark Ransom Jul 31 '12 at 19:58
  • $\begingroup$ yeah read , the Wikipedia Gamma Correction focuses on the input signal to output signal relation being Nonlinear and thus presents it in this way But I want Explanation in terms of Image Enhancement Aspect ,and want to clarify if this procedure passes to become Gamma Correction. $\endgroup$ – Deepak kumar Jha Jul 31 '12 at 20:00