Sparse Representations-based depth images quality assessment-Reference-Cited by-同舟云学术

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Sparse Representations-based depth images quality assessment

Published:2021-03 Issue:1 Volume:5 Page:67-75
ISSN:2468-502X
Container-title:Visual Informatics
language:en
Short-container-title:Visual Informatics

Author:

Sebai Dorsaf^ORCID,Sehli Maryem,Ghorbel Faouzi

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Human-Computer Interaction,Software

Reference47 articles.

1. Sparse and redundant modeling of image content using an image-signature-dictionary;Aharon;SIAM J. Imaging Sci.,2008

2. The K-SVD: an algorithm for designing of overcomplete dictionaries for sparse representations;Aharon;IEEE Trans. Signal Process.,2006

3. Comparison of image quality assessment: PSNR, HVS, SSIM, UIQI;Al-Najjar;Int. J. Sci. Eng. Res.,2012

4. A Human Visual System Based 3D Video Quality Metric;Banitalebi-Dehkordi,2013

5. 3D Video quality metric for 3D video compression;Banitalebi-Dehkordi,2013

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. End-to-End Variable-Rate Learning-Based Depth Compression Guided by Deep Correlation Features;Journal of Signal Processing Systems;2024-01

2. WeLDCFNet: Convolutional Neural Network based on Wedgelet Filters and Learnt Deep Correlation Features for depth maps features extraction;2022 IEEE 24th International Workshop on Multimedia Signal Processing (MMSP);2022-09-26

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