@conference {13609,
	title = {No-reference image quality assessment based on visual codebook},
	booktitle = {Image Processing (ICIP), 2011 18th IEEE International Conference on},
	year = {2011},
	month = {2011/09//},
	pages = {3089 - 3092},
	abstract = {In this paper, we propose a new learning based No-Reference Image Quality Assessment (NR-IQA) algorithm, which uses a visual codebook consisting of robust appearance descriptors extracted from local image patches to capture complex statistics of natural image for quality estimation. We use Gabor filter based local features as appearance descriptors and the codebook method encodes the statistics of natural image classes by vector quantizing the feature space and accumulating histograms of patch appearances based on this coding. This method does not assume any specific types of distortion and experimental results on the LIVE image quality assessment database show that this method provides consistent and reliable performance in quality estimation that exceeds other state-of-the-art NR-IQA approaches and is competitive with the full reference measure PSNR.},
	keywords = {assessment;quality, codebook;Gabor, descriptors;complex, estimation;visual, extraction;image, filter;appearance, filters;feature, gabor, image, image;no-reference, patches;natural, QUALITY, statistics;local, texture;},
	doi = {10.1109/ICIP.2011.6116318},
	author = {Ye,Peng and David Doermann}
}
@conference {11975,
	title = {Robust Contrast Invariant Stereo Correspondence},
	booktitle = {Proceedings of the 2005 IEEE International Conference on Robotics and Automation, 2005. ICRA 2005},
	year = {2005},
	month = {2005/04/18/22},
	pages = {819 - 824},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {A stereo pair of cameras attached to a robot will inevitably yield images with different contrast. Even if we assume that the camera hardware is identical, due to slightly different points of view, the amount of light entering the two cameras is also different, causing dynamically adjusted internal parameters such as aperture, exposure and gain to be different. Due to the difficulty of obtaining and maintaining precise intensity or color calibration between the two cameras, contrast invariance becomes an extremely desirable property of stereo correspondence algorithms. The problem of achieving point correspondence between a stereo pair of images is often addressed by using the intensity or color differences as a local matching metric, which is sensitive to contrast changes. We present an algorithm for contrast invariant stereo matching which relies on multiple spatial frequency channels for local matching. A fast global framework uses the local matching to compute the correspondences and find the occlusions. We demonstrate that the use of multiple frequency channels allows the algorithm to yield good results even in the presence of significant amounts of noise.},
	keywords = {Apertures, Calibration, CAMERAS, Computer science, contrast invariance, diffusion, Educational institutions, Frequency, gabor, Hardware, occlusions, Robot vision systems, Robotics and automation, Robustness, stereo},
	isbn = {0-7803-8914-X},
	doi = {10.1109/ROBOT.2005.1570218},
	author = {Ogale, A. S and Aloimonos, J.}
}
