Multiscale Retinex Technique with Color Correction Based on the Retinex Theory

1. Multiscale Retinex Technique with Color Correction Based on the Retinex Theory

2. Retinex Image Enhancement • Edward Land’86 • There exists a discrepancy between the human vision system and the recorded color images. • Dynamic range difference results in the loss of the essentials features from the recorded images. • Improved fidelity of color images to human observation can be obtained by (a) Computation that combines dynamic range compression, color constancy and color rendition (b) Color restoration.

3. Block Diagram | | | | | | | | | | | | | | | | I(x,y) MSR Log W1 * F1(x,y) - W2 + + * + Log Gain/ offset Σ Σ MSRCR F2(x,y) W3 + * F3(x,y) α CRF CR Log

4. Design of Surround Function • First proposed design of Surround function by E.Land’86 was inverse square spatial surround F(x,y) = 1/ [1+(r2 + c2)] • The surround function was later modified in Gaussian form by Hurlbert’89 F(x,y) = exp(-r2 / c2 ) Where r- √ x2 + y2 and c- Surround Space Constant

5. Single scale Retinex Method The Single Scale retinex is given by Ri (x,y)=log Ii (x,y) – log [F(x,y) * Ii (x,y) ] Where F(x,y) = K exp(-r2 / c2 )--- Surround Function c- Scalar value and selection of K is that r- √ x2 + y2 ∫∫ F(x,y) dx dy =1

6. Multiscale Retinex Method The multi-scale retinex is represented by Ri (x,y)= Σ Wn { log Ii (x,y) - log[ F(x,y) * Ii (x,y) ]} Where n -- Scaling Factor Wn – Weights (1/3 for each color channel of RGB) N n=1 http://dragon.larc.nasa.gov/pub/papers/multsclrtx.pdf

7. Limitations of MSR Limitations of the MSR: • The Selection of the value of ‘c’ in equ(1) is critical. • The DRC results in the violation of Gray world algorithm • The region of constant color bleaches out as a result of DRC. Gray World Assumptions: Gray World Assumption states is that, given an image with sufficient amount of color variations, the average value of the RED, GREEN, and BLUE components of the image should average out to a common gray value.

8. Color Restoration The color restoration is calculated using the expression Ci(x,y) = β{log[α Ii (x,y)] – log[ ΣIi(x,y)]} Where β- Gain Constant α- Controls the strength of non-linearity The Final representation of MSRCR is represented as R MSRCRi (x, y) = G [Ci (x, y) * RMSRi (x, y) + b] Where G- Gain Constant and b- Gain Offset value s i=1

9. ALGORITHM-I RESULTS

10. Constants Values Applied in Retinex Wn - 1/3 - Weight used in Multiscale Retinex N – Number of Scale =3 C1, C2, C3 - Surround Constant – 15, 80,250 respectively G - Final Gain – 192 b - Offset Value – 30 α – Strength of non-linearity – 125 β – Control gain constant - 46

11. Surround Function Gaussian Surround Function F(r) Image Co-ordinate

12. Results of SSR Space Constant c=80 Input Output

13. Results of SSR Space Constant c=80 Inputs Outputs

14. Results of SSR Outputs Inputs c=15 c=80 c=215

15. Results of MSRCR Output of MSRCR: Inputs MSR Output MSRCR Output

16. Results of MSRCR Tak at IRIS Laboratory: Inputs MSR Output MSRCR Output

17. Results of MSRCR Tak at McGhee Tyson Airport: Inputs MSR Output MSRCR Output

18. Comparison- Available Software and My Implementation Few Examples: Input Software My results

19. Comparison- Available Software and My Implementation Tak at IRIS and McGhee Tyson Airport: Input Software My results

20. Comparison- Available Software and My Implementation The following image was presented as an example in the paper, the same image is used as input to both the software available and my implementation. My Implementation From Available Software Test Image http://dragon.larc.nasa.gov/pub/papers/multsclrtx.pdf