Young Researchers in Imaging Science: Modelling and Algorithms

A special issue of Algorithms (ISSN 1999-4893).

Deadline for manuscript submissions: closed (15 June 2022) | Viewed by 1808

Special Issue Editor


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Guest Editor
Department of Mathematics, University of Bologna, 40126 Bologna, Italy
Interests: numerical analysis engineering; applied and computational mathematics; modeling and simulation; numerical simulation

Special Issue Information

Dear colleagues,

We invite you to submit your research in the field of imaging inverse problems to the Special Issue ‘Young Researchers in Imaging Science: modelling and algorithms’. In the last few decades, images have become one of the most widespread means of communication. The main reason behind this increasing diffusion is the variety of different applications involving data that can be rearranged so as to be visualized as images. Image processing methods are aimed at developing strategies for manipulating, transmitting and even improving two-dimensional signals.

The goal of the Special Issue is to collect the latest advances concerning the design of novel flexible models, as well as efficient and robust algorithmic procedures to address imaging inverse problems from a variational, statistical and learning perspective.

We highly encourage submissions authored by young researchers or with a young researcher as first author. In fact, this Special Issue represents an opportunity for PhD students, post-doctorate fellows and early-career researchers to share their results with the imaging community.

Dr. Monica Pragliola
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (1 paper)

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15 pages, 9279 KiB  
Article
A Coupled Variational System for Image Decomposition along with Edges Detection
by Jianlou Xu, Yuying Guo, Yan Hao and Leigang Huo
Algorithms 2022, 15(8), 288; https://doi.org/10.3390/a15080288 - 16 Aug 2022
Viewed by 1470
Abstract
In order to better decompose the images and protect their edges, in this paper, we proposed a coupled variational system consisting of two steps. The first step, an improved weighted variational model is introduced to obtain the cartoon and texture. Using the obtained [...] Read more.
In order to better decompose the images and protect their edges, in this paper, we proposed a coupled variational system consisting of two steps. The first step, an improved weighted variational model is introduced to obtain the cartoon and texture. Using the obtained cartoon image, in the second step, a new vector function is obtained for describing the pseudo edge of the considered image by one Tikhonov regularization variational model. Because Tikhonov regularization model is equivalent to carrying out a Gaussian linear filtering, the obtained vector function is smoother. To solve the coupled system, we give the alternating direction method, primal-dual method and Gauss-Seidel iteration. Using the coupled system, we can not only separate out the cartoon and texture parts, but also extract the edge. Extensive numerical experiments are given to show the effectiveness of the proposed method compared with other variational methods. Full article
(This article belongs to the Special Issue Young Researchers in Imaging Science: Modelling and Algorithms)
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