Online Adaptive Image Reconstruction (OnAIR) Using Dictionary Models
نویسندگان
چکیده
منابع مشابه
Tomographic Image Reconstruction using Dictionary Priors
We describe and examine an algorithm for tomographic image reconstruction where prior knowledge about the solution is available in the form of training images. We first construct a nonnegative dictionary based on prototype elements from the training images; this problem is formulated as a regularized non-negative matrix factorization. Incorporating the dictionary as a prior in a convex reconstr...
متن کاملSpeech Enhancement using Adaptive Data-Based Dictionary Learning
In this paper, a speech enhancement method based on sparse representation of data frames has been presented. Speech enhancement is one of the most applicable areas in different signal processing fields. The objective of a speech enhancement system is improvement of either intelligibility or quality of the speech signals. This process is carried out using the speech signal processing techniques ...
متن کاملSupervised Online Dictionary Learning for Image Separation Using OMP
In this paper, we propose a new algorithm to perform single image separation based on online dictionary learning and orthogonal matching pursuit (OMP). This method consists of two separate processes: dictionary training for representing morphologically different components and the separation stage. The training process takes advantage of the prior knowledge of the components by adding component...
متن کاملAdaptive Image Reconstruction Using Information Measures
We present a class of nonlinear adaptive image restoration filters which may be steered to preserve sharp edges and contrasts in the restorations. From a theoretical point of view we discuss the associated variational problems and prove existence of solutions in certain Sobolev spaces W 1,p or in a BV -space. The degree of regularity of the solution may be understood as a mathematical explanati...
متن کاملAn Adaptive Image Reconstruction Method an Adaptive Image Reconstruction Method
A new adaptive regression type of image destriping method is introduced to reconstruct missing lines in mul-tispectral images. The method uses available information from the failed pixel surrounding due to spectral and spatial correlation of multispectral data. The reconstruction is based on two mutually competing adaptive regression models from which the locally optimal predictor is selected.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Computational Imaging
سال: 2020
ISSN: 2333-9403,2334-0118,2573-0436
DOI: 10.1109/tci.2019.2931092