We present a novel formulation of exemplar-based inpainting as a global energy optimization problem, written in terms of the offset map. The proposed energy function combines a data attachment term that ensures the continuity of reconstruction at the boundary of the inpainting domain with a smoothness term that ensures a visually coherent reconstruction inside the hole. This formulation is adapted to obtain a global minimum using the graph cuts algorithm. To reduce the computational complexity, we propose an efficient multiscale graph cuts algorithm. To compensate the loss of information at low resolution levels, we use a feature representation computed at the original image resolution. This permits alleviation of the ambiguity induced by comparing only color information when the image is represented at low resolution levels. Our experiments show how well the proposed algorithm performs compared with other recent algorithms.
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http://dx.doi.org/10.1109/TIP.2012.2218828 | DOI Listing |
PLoS One
January 2025
Computer Science and Engineering Discipline, Khulna University, Khulna, Bangladesh.
The objective of the max-cut problem is to cut any graph in such a way that the total weight of the edges that are cut off is maximum in both subsets of vertices that are divided due to the cut of the edges. Although it is an elementary graph partitioning problem, it is one of the most challenging combinatorial optimization-based problems, and tons of application areas make this problem highly admissible. Due to its admissibility, the problem is solved using the Harris Hawk Optimization algorithm (HHO).
View Article and Find Full Text PDFIn this paper, we consider two fundamental cut approximation problems on large graphs. We prove new lower bounds for both problems that are optimal up to logarithmic factors. The first problem is to approximate cuts in balanced directed graphs.
View Article and Find Full Text PDFEur Radiol
November 2024
Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile.
Objective: To estimate proton density fat fraction (PDFF) from chemical shift encoded (CSE) MR images using a deep learning (DL)-based method that is precise and robust to different MR scanners and acquisition echo times (TEs).
Methods: Variable echo times neural network (VET-Net) is a two-stage framework that first estimates nonlinear variables of the CSE-MR signal model, to posteriorly estimate water/fat signal components using the least-squares method. VET-Net incorporates a vector with TEs as an auxiliary input, therefore enabling PDFF calculation with any TE setting.
Sci Rep
October 2024
Department of Mathematics, Panimalar Engineering College, Chennai, 600123, India.
Yeast
October 2024
Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail), Rennes, France.
Saccharomyces cerevisiae is an excellent model to study the effect of external cues on cell division and stress response. 5-Fluorocuracil (5-FU) has been used to treat solid tumors since several decades. The drug was initially designed to interfere with DNA replication but was later found to exert its antiproliferative effect also via RNA-dependent processes.
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