Image feature subsets for predicting the quality of consumer camera images and identifying quality dimensions-Reference-Cited by-同舟云学术

Image feature subsets for predicting the quality of consumer camera images and identifying quality dimensions

Published:2014-09-15 Issue:6 Volume:23 Page:061111
ISSN:1017-9909
Container-title:Journal of Electronic Imaging
language:en
Short-container-title:J. Electron. Imaging

Author:

Nuutinen Mikko¹,Virtanen Toni²,Oittinen Pirkko³

Affiliation:

1. Aalto University, Department of Media Technology, P.O. Box 15500, Espoo FI-00076, FinlandbUniversity of Helsinki, Institute of Behavioural Sciences, P.O. Box 9, Helsinki FI-00014, Finland

2. University of Helsinki, Institute of Behavioural Sciences, P.O. Box 9, Helsinki FI-00014, Finland

3. Aalto University, Department of Media Technology, P.O. Box 15500, Espoo FI-00076, Finland

Publisher

SPIE-Intl Soc Optical Eng

Subject

Electrical and Electronic Engineering,Computer Science Applications,Atomic and Molecular Physics, and Optics

Cited by 9 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. Review of Quality Assessment Algorithms on the Realistic Blurred Image Database (BID2011);2023 8th International Conference on Signal and Image Processing (ICSIP);2023-07-08

2. A hybrid indicator for realistic blurred image quality assessment;Journal of Visual Communication and Image Representation;2023-06

3. FFTMI: Features Fusion for Natural Tone-Mapped Images Quality Evaluation;IEEE Transactions on Multimedia;2020-08

4. Blind Image Quality Assessment Using Statistical Structural and Luminance Features;IEEE Transactions on Multimedia;2016-12

5. Blind quality index for camera images with natural scene statistics and patch-based sharpness assessment;Journal of Visual Communication and Image Representation;2016-10