NUMERICAL COMPARISON OF DIFFERENT IMAGING ALGORITHMS.
Image processing is the set of operations performed to extract
“information” from the image. An interesting problem in digital image
processing is the restoration of degraded images. It often happens that
the resulting image is different from the expected image. Our problem
will therefore be to recover an image close to the original image from a
poor quality image (that has been skewed by Gaussian and additive
noise). There are a lot of algorithms on how we can improve the broken
image in better quality. We present in this paper our numerical results
obtained with the models of Tichonov regularization, ROF, Vese Osher,
anisotropic and isotropic TV denoising algorithms.