Space Variant Blind Image Restoration

Space Variant Blind Image Restoration

In this report, we are interested in blind restoration of optical images that are degraded by a space-variant (SV) blur and corrupted with Poisson noise. For example, blur variation is due to refractive index mismatch in three dimensional fluorescence microscopy or due to atmospheric turbulence in astrophysical images. In our work, the SV Point Spread Function (PSF) is approximated by a convex ...

Image Restoration by Variable Splitting based on Total Variant Regularizer

The aim of image restoration is to obtain a higher quality desired image from a degraded image. In this strategy, an image inpainting method fills the degraded or lost area of the image by appropriate information. This is performed in such a way so that the obtained image is undistinguishable for a casual person who is unfamiliar with the original image. In this paper, different images are degr...

Space-Variant Image Restoration with Running Sinusoidal Transforms

Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake

Modelling camera shake as a space-invariant convolution simplifies the problem of removing camera shake, but often insufficiently models actual motion blur such as those due to camera rotation and movements outside the sensor plane or when objects in the scene have different distances to the camera. In an effort to address these limitations, (i) we introduce a taxonomy of camera shakes, (ii) we...

Blind Image Deconvolution using a Space-variant Neural Network Approach

A space variant neural network based on an autoregressive moving average (ARMA) process is proposed for blind image deconvolution. An extended cost function motivated by human visual perception is developed to simultaneously identify the blur and restore the image degraded by space variant non-causal blur and additive white Gaussian noise (AWGN). Since the blur affects various regions of the im...