**PURPOSE**- Applies graduated non-convex restoration algorithm to an image. Example.

**SEE ALSO****CE FIT**[Contrast Enhancement - FIT the histogram] **CE MED**[Contrast Enhancement - Median Filtering]

**USAGE**- .OPERATION: CE GNC

- .INPUT FILE: PIC001

[Enter name of picture to be processed.].OUTPUT FILE: PIC002

[Enter name of file receiving the output picture.].LAMBDA: 3

[The parameter*LAMBDA*is a characteristic length or 'scale'. The lower*LAMBDA*, the finer the structure that is found.].H0: 0.02

[The ratio*H0 [=sqrt(2*alpha/LAMBDA)]*is a 'contrast' sensitivity threshold determining the minimum contrast for detection of an isolated step edge. A step edge in the data counts as isolated if there are no features within a distance*LAMBDA*of it.].EPS: 1.0E-8

[*EPS*indicates the accuracy of restoration. The smaller*EPS*, the longer computation time. Reasonable results can be obtained for*EPS<=1.0E-7*]

**NOTES**

- The ratio
*g = H0/(2*LAMBDA)*is a limit on the gradient above which spurious discontinuities may be generated. If the gradient exceeds*g,*one or mores discontinuities may appear in the fitted function. - The parameter
*alpha*is a measure of immunity to noise. If the mean noise has standard dev.*sigma*, then no spurious discontinuities are generated provided*alpha>2*sigma**2*, approximately. - This program is highly recommended for restoration of noisy pictures.
It applies a graduated non-convex algorithm to find the solution
of the weak continuity constraints problem for a given picture. Weak
continuity constraints prefer continuity, but allow occasional
discontinuities if that makes for a simpler overall description.
For a detailed discussion of the method and parameters values
look in
*Visual Reconstruction*, Andrew Blake & Andrew Zisserman. - Implemented by: Paul Penczek.

**SUBROUTINES**- GNC, GNC2S, GP, ERC

**CALLER**- UTIL2

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