Constrained Image Restoration with

Non-Lipschitz lp-Regularization and Box Constrained Model for Image Restoration

Nonsmooth nonconvex regularization has remarkable advantages for the restoration of piecewise constant images. Constrained optimization can improve the image restoration using a priori information. In this paper, we study regularized nonsmooth nonconvex minimization with box constraints for image restoration. We present a computable positive constant θ for using nonconvex nonsmooth regularizat...

Nonconvex `p -regularization and Box Constrained Model for Image Restoration

Abstract. Nonsmooth nonconvex regularization has remarkable advantages for the restoration of piecewise constant images. Constrained optimization can improve the image restoration using a priori information. In this paper, we study regularized nonsmooth nonconvex minimization with box constraints for image restoration. We present a computable positive constant θ for using nonconvex nonsmooth re...

Bayesian Image Restoration and Segmentationby Constrained

A constrained optimization method, called the Lagrange-Hoppeld (LH) method, is presented for solving Markov random eld (MRF) based Bayesian image estimation problems for restoration and segmentation. The method combines the augmented Lagrangian mul-tiplier technique with the Hoppeld network to solve a constrained optimization problem into which the original Bayesian estimation problem is reform...

Li : Map Image Restoration and Segmentation by Constrained Optimization 3

Image Restoration Using A PDE-Based Approach

 Image restoration is an essential preprocessing step for many image analysis applications. In any image restoration techniques, keeping structure of the image unchanged is very important. Such structure in an image often corresponds to the region discontinuities and edges. The techniques based on partial differential equations, such as the heat equations, are receiving considerable attention i...

Blocking effect reduction of compressed images using classification-based constrained optimization

In this paper we propose an adaptive image restoration algorithm using block-based edge-classi"cation for reducing block artifacts in compressed images. In order to e$ciently reduce block artifacts, edge direction of each block is classi"ed by using model-"tting criterion, and the constrained least-squares (CLS) "lter with corresponding direction is used for restoring the block. The proposed re...