1 / 23

Approaches for Retinex and Their Relations

Approaches for Retinex and Their Relations. Yu Du March 14, 2002. Presentation Outline. Introductions to retinex Approaches for retinex The variational framework Relation of these approaches Conclusions. What Is Retinex. Lightness and retinex theory E. H. Land 1971

evita
Download Presentation

Approaches for Retinex and Their Relations

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Approaches for Retinex and Their Relations Yu Du March 14, 2002

  2. Presentation Outline • Introductions to retinex • Approaches for retinex • The variational framework • Relation of these approaches • Conclusions

  3. What Is Retinex • Lightness and retinex theory • E. H. Land 1971 • Visual system of human • Retina: the sensory membrane lining the eye that receives the image formed by the lens (Webster) • Reflectance and illumination • Edges and independent color senstion

  4. Model of retinex (1) The given image The illumination part The reflectance part

  5. Model of retinex (2) + Log Exp Input Image Estimate the Illumination

  6. Three Types of Previous Approaches • Random walk algorithms • E. H. Land (1971) • Homomorphic filtering • E. H. Land (1986), D. J. Jobson (1997) • Solving Poisson equation • B. K. P. Horn (1974)

  7. Random Walk Algorithms (1) • First retinex algorithm • A series of random paths • Starting pixel • Randomly select a neighbor pixel as next pixel on path • Accumulator and counter

  8. Random Walk Algorithms (2) • Adequate number of random paths • Cover the whole image • Small variance • Length of paths • >200 for 10x10 image (D. H. Brainard)

  9. Special Smoothness of Random Walk • The value in the accumulator • The illumination part

  10. Homomorphic Filtering • Assume illumination part to be smooth • Apply low pass filter

  11. Poisson Equation Solution (1) • Derivative of illumination part close to zero • Reflectance part to be piece-wise constant • Get the illumination part • Take the derivative of the image • Clip out the high derivative peaks

  12. Poisson Equation Solution (2) • Solve Poisson equation • Iterative method • Apply low-pass filter (invert Laplacian operator)

  13. Comments on Above Approaches • Random walk algorithm • Too slow • Homomorphic filtering • Low-pass filtering first or log first? • More work needed to be done on Poisson equation solving

  14. Variational Framework • Presented by R. Kimmel etc. • From assumptions to penalty function • From penalty function to algorithm

  15. Assumptions On Illumination Image • Spatial smoothness of illumination • Reflectance is not pure white • Illumination close to intensity image • Spatial smoothness of reflectance • Continues smoothly beyond boundaries

  16. Penalty Function and Restrictions • Goal to minimize: • Subject to: And on

  17. Solve the Penalty Function (1) • Euler-Lagrange equations And

  18. Solve the Penalty Function (2) • Projected normalized steepest descent (PNSD) • Iteratively to get illumination part

  19. Multi-resolution • Make PNSD algorithm converges faster • Illumination part is smooth • Coarse resolution image first • Upscale coarse illumination as initial of finer resolution layer • Not multi-scale technique

  20. Relationship of Different Approaches (1) • Random walk and Homomorphic filtering • R. Kimmel’s words on Homomorphic filtering and remove constraint

  21. Relationship of Different Approaches (2) • Apply appropriate scaling on images, Homomorphic filtering satisfies constrain and • Poisson equation approach:

  22. Conclusions • Retinex is trying to simulate human vision process • Different approaches are from same assumptions • Implementation details are important for results

  23. Thank You March 14, 2002

More Related