Blind image quality assessment based on the multiscale and dual‐domains features fusion-Reference-Cited by-同舟云学术

Blind image quality assessment based on the multiscale and dual‐domains features fusion

Published:2021-02-22 Issue: Volume: Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Lu Yaxuan¹²³⁴,Li Weijun¹²³⁴,Ning Xin¹²³⁴,Dong Xiaoli¹²³⁴,Zhang Liping¹²³⁴,Sun Linjun¹²³⁴,Cheng Chuantong¹

Affiliation:

1. Institute of Semiconductors Chinese Academy of Sciences Beijing China

2. Beijing Key Laboratory of Semiconductor Neural Network Intelligent Sensing and Computing Technology Beijing China

3. School of Microelectronics University of Chinese Academy of Sciences Beijing China

4. Cognitive Computing Technology Joint Laboratory Wave Group Beijing China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6177

Reference38 articles.

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2. RenH ChenD WangY RAN4IQA: restorative adversarial nets for no‐reference image quality assessment. Paper presented at: Proceedings of the Conference Artificial Intelligence New Orleans LA;2018:7308‐7314.

3. Image Quality Assessment: From Error Visibility to Structural Similarity

4. FSIM: A Feature Similarity Index for Image Quality Assessment

5. A Two-Step Framework for Constructing Blind Image Quality Indices

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