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CVPR
2012
IEEE
10 years 14 hour ago
Unsupervised feature learning framework for no-reference image quality assessment
In this paper, we present an ef´Čücient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...
Peng Ye, Jayant Kumar, Le Kang, David S. Doermann
ICIP
2007
IEEE
12 years 11 months ago
Iterative Blind Image Motion Deblurring via Learning a No-Reference Image Quality Measure
In this paper, we propose a learning-based image restoration algorithm for restoring images degraded by uniform motion blurs. The motion blur parameters are first approximately es...
Wen-Hao Lee, Shang-Hong Lai, Chia-Lun Chen
HVEI
2010
11 years 7 months ago
No-reference image quality assessment based on localized gradient statistics: application to JPEG and JPEG2000
This paper presents a novel system that employs an adaptive neural network for the no-reference assessment of perceived quality of JPEG/JPEG2000 coded images. The adaptive neural ...
Hantao Liu, Judith Redi, Hani Alers, Rodolfo Zunin...
CVPR
2008
IEEE
12 years 11 months ago
Unsupervised estimation of segmentation quality using nonnegative factorization
We propose an unsupervised method for evaluating image segmentation. Common methods are typically based on evaluating smoothness within segments and contrast between them, and the...
Roman Sandler, Michael Lindenbaum
CVPR
2010
IEEE
12 years 27 days ago
Classification and Clustering via Dictionary Learning with Structured Incoherence
A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that best fit the data, ...
Pablo Sprechmann, Ignacio Ramirez, Guillermo Sapir...
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