Issue No. 01 - January/February (2011 vol. 31)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCG.2010.105
Many example-based imageprocessing algorithms operate on image patches (texture synthesis, resolution enhancement, image denoising, and so on). However, inaccessibility to a large, varied collection of image patches has hindered widespread adoption of these methods. The authors describe the construction of a database of one trillion image patches and demonstrate its research utility.
Databases, Approximation methods, Approximation algorithms, Nearest neighbor searches, Accuracy, Image segmentation, Artificial neural networks,graphics and multimedia, natural images, image processing, nearest neighbor, image patches, image databases, kd-trees, locality-sensitive hashing, LSH, distributed processing, image search, computer graphics
S M Arietta, J Lawrence, "Building and Using a Database of One Trillion Natural-Image Patches", IEEE Computer Graphics and Applications, vol. 31, no. , pp. 9-19, January/February 2011, doi:10.1109/MCG.2010.105