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» Robust approach for color image quality assessment
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CVPR
2012
IEEE
11 years 11 months ago
Unsupervised feature learning framework for no-reference image quality assessment
In this paper, we present an efficient 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
ICMCS
2007
IEEE
117views Multimedia» more  ICMCS 2007»
14 years 2 months ago
Learning-Based Perceptual Image Quality Improvement for Video Conferencing
It is well known that in professional TV show filming, stage lighting has to be carefully designed in order to make the host and the scene look visually appealing. The lighting a...
Zicheng Liu, Cha Zhang, Zhengyou Zhang
ISM
2006
IEEE
104views Multimedia» more  ISM 2006»
14 years 2 months ago
A Novel Invisible Color Image Watermarking Scheme Using Image Adaptive Watermark Creation and Robust Insertion-Extraction
In this paper we present a robust and novel strategic invisible approach for insertion-extraction of a digital watermark, a color image, into color images. The novelty of our sche...
Saraju P. Mohanty, Parthasarathy Guturu, Elias Kou...
ICIP
2002
IEEE
14 years 10 months ago
No-reference perceptual quality assessment of JPEG compressed images
Human observers can easily assess the quality of a distorted image without examining the original image as a reference. By contrast, designing objective No-Reference (NR) quality ...
Hamid R. Sheikh, Zhou Wang, Alan C. Bovik
ISBI
2004
IEEE
14 years 9 months ago
Image-Quality Assessment in Optical Tomography
Modern medical imaging systems often rely on complicated hardware and sophisticated algorithms to produce useful digital images. It is essential that the imaging hardware and any ...
Matthew A. Kupinski, Eric Clarkson