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Honest Image Thumbnails: Algorithm and Subjective Evaluation
Samadani, Ramin; Mauer, Tim; Berfanger, David; Clark, Jim; Lim, Suk Hwan; Tretter, Dan
Keyword(s): image thumbnails; image quality; image browsing; blur; noise
Abstract: Image thumbnails are commonly used for selecting images for display, sharing or printing. Current, standard thumbnails do not distinguish between high and low quality originals. Both sharp and blurry originals appear sharp in the thumbnails, and both clean and noisy originals appear clean in the thumbnails. This leads to errors and inefficiencies during image selection. In this paper, thumbnails generated using image analysis better represent the local blur and the noise of the originals. The new thumbnails provide a quick, natural way for users to identify images of good quality, while allowing the viewer.s knowledge to select desired subject matter. A subjective evaluation using twenty subjects shows the new thumbnails are more representative of their originals for blurry images. In addition, there are no significant differences between the results of the new thumbnails and the standard thumbnails for clean images. The noise component improves the results for noisy images, but degrades the results for textured images. The blur component of the new thumbnails may always be used. The decision to use the noise component of the new thumbnails should be based on testing with the particular image mix expected for the application.
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