1. Blind Inverse Gamma Correction (Hany Farid, IEEE Trans. Signal Processing, vol. 10 no. 10, October 2001) An article review Merav Kass January 2003

2. Imaging device non linearity character. Gamma correction: Inverse gamma correction – an advantageous to SP applications. Inverse Gamma Correction - Motivation

3. If  is known: blind inverse gamma correction The need in blind inverse gamma correction arise! Typically,  is determined experimentally. The imaging device calibration information Blind Inverse Gamma Correction - Motivation

4. What is a blind inverse Gamma correction ? It is an estimation process. No prior knowledge is assumed. How does it work ? Minimize higher-order correlation in the frequency domain. What? & How?

5. Original Signal Modified Signal Gamma Correction Higher Order Correlation

6. Higher order correlations in the frequency domain Deviation of Gamma from unity Gamma Higher order correlations 1

7. How higher order correlations can be measured ? By estimating the bicoherence function: It reveals the sort of higher order correlations introduced by nonlinearity.

8. Assumptions Only one parameter has to be estimated : gamma. The only thing we have to work with is the a gamma corrected image. The Algorithm

9. Course of action Apply inverse Operation Measure Correlations The Algorithm

10. Experimental Results BeforeAfter  = 0.42  = 0.80  = 1.10  = 1.63  = 2.11 On Average, the correct gamma is estimated within 7.5% of the actual value.

11. C(  ) is a well behaved function. Calculation efficiency. The algorithm performance in presence of additive noise. The algorithm performance in presence of linear transformations. Colored images. Additional Notes

12. One parameter model is assumed. The procedure assume to be uniform. Restrictions and Limitations