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About Image Inpainting Using Non-Negative Matrix Factorization
This document summarizes a research article that proposes a novel non-blinded image inpainting algorithm using low rank non-negative matrix factorization (NMF). The algorithm aims to improve efficiency of exemplar-based inpainting by reducing the global search space dimension using information from neighbor patches surrounding the target region. Neighbor patches that have full pixel information are introduced and their structural and textural properties are used to approximate the target region through NMF, which seeks low-dimensional representations of non-negative matrices. This avoids needing a weight matrix or sparse representations used in previous methods. The proposed algorithm shows comparable inpainted image quality to other techniques while improving computational efficiency.
Detailed Information
| Author: | ['a.akbar'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 6 |
| Language: | English |
| Format: | |
| Price: | FREE |
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