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Found 5 papers, 0 papers with code
Image denoising based on improved data-driven sparse representation
Instead of adopting fixed filters for constructing a tight frame to sparsely model any input image, a data-driven tight frame was proposed for the sparse representation of images, and shown to be very efficient for image denoising very recently.
Inexact Alternating Direction Method Based on Newton descent algorithm with Application to Poisson Image Deblurring
The recovery of images from the observations that are degraded by a linear operator and further corrupted by Poisson noise is an important task in modern imaging applications such as astronomical and biomedical ones.
Fixed Point Algorithm Based on Quasi-Newton Method for Convex Minimization Problem with Application to Image Deblurring
The novel method is derived from the idea of the quasi-Newton method, and the fixed-point algorithms based on the proximity operator, which were widely investigated very recently.
Novel variational model for inpainting in the wavelet domain
Wavelet domain inpainting refers to the process of recovering the missing coefficients during the image compression or transmission stage.
Fast Linearized Alternating Direction Minimization Algorithm with Adaptive Parameter Selection for Multiplicative Noise Removal
Owing to the edge preserving ability and low computational cost of the total variation (TV), variational models with the TV regularization have been widely investigated in the field of multiplicative noise removal.
