Image Restoration and Inpainting: MinGW/OpenGL/Visual c++/Java image processing enhancing/restoring/detecting/recovering image parts(Old painting cracks...) FastRestorarion, 2D (Un)Splitted Linear Solver, nonlinear solver: conjugate gradient,QuasiNewton

restoreInpaint is a state of the art project about making 8 or 16bit depth images "better":

Image Restoration and Inpainting: MinGW/OpenGL/Visual c++/Java image processing enhancing/restoring/detecting/recovering image parts(Old painting cracks...) FastRestorarion, 2D (Un)Splitted Linear Solver, nonlinear solver: conjugate gradient,QuasiNewton

* Detection covers the problem of finding target areas
* Inpainting discovers the problem of filling detected cracks and missing thin parts of images, paintings, frescos.
* Restoration allows the recovery of an image, removing noise, enhancing brightness, color and details. Usage: paintings, pictures improvements.
* Realtime and Fast Restorations are used with large images, like in medical imaging and astronomy. Details are restored via distance modulated restorations
* Semi-Implicit/Implicit Solvers ~40 fast C++ linear solvers:Direct/BB/Conjugate Gradient> used with LOD/AOS/.../ADI + BE/Crank Nicolson.
* NEW Fixed Point Solvers can be used in restorations like TVn1, TVnm, TVtrace and (WeberTV) edge preserving restorations.
* New Image Reconstructions Deblurring images allows image reconstruction from low quality data.
* NEW Large Nonlinear Solver Bench: 22 NonlinearCG: HS+,FR,PRP+,CD,Perry,LS,DL,DY,HS-DY,CD-HS,YT,YS,HZ,Grippo-PRP; Spectral solvers: BB, Birgins-Martinez SPG; Large Scale Quasi-Newton: Shanno-Phua CG, Andrei ScaleCG, Limited-BFGS; 11 Line Search: Secant, Backtraking, Backstepping, Wolf: MoreThuente, CONMIN, Denis, standart, approximated, nonmonotone. Available: MathBidouble 1.2a

Restoration

A large number of restoration techniques will be used in this framework. They will help people to recover images of different kind. Also it is wise that people will select themselve the suitable restoration method:
o People interested in general information, will blur the image.
o People looking for getting clean images, will go for getting smooth images.
o People looking for getting clean images with clear borders, will smooth the images and maintain borders.
o People requiring details will enhance details.
o Deciders an consultants requiring direct on spot examples.Java in a browser presentations
o OO developer will fly with Tornado1.2, flexible restoration C++ classes completely freely.

Inpainting

The framework provides seven inpaintings with additional detection capabilities. People will be able to detect/remove thin artifacts, characters printed on pictures....
o First, the user provides the inpainting area or uses an image crack detector.
o With the known area, the inpainting will fill the gap using sophisticated techniques including:
+ Transportation used to move pixels from outside to inside cracks, taking account the details of the neigbour pixels.
+ Diffusion propagates your pixels from cracks borders, like something hot(the image) moves into a cold area(the crack area).
+ Multiresolution Looking to smaller images first will ease the inpainting. The results are propagated to larger scales images.

Tornado1: General Purpose Linear Solvers (NEW)

Fast restoration can be tried in 100 ways, Today. Tornado1 concept is a spt restoration framework using advanced linear solvers: All solvers support tridiagonals and any band matrices.
Solvers like the Thomas direct solver, advanced Barzilai-Borwein, and number of CG and Krylov solvers are available, making comparision easy. Nearly all can be used with 2D splitted or unsplitted methods.(Thomas use only tridiagonals)
The solvers may be used in general purpose applications.

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