Yet Another Computer Vision Index To Datasets (YACVID) - Details

Stand: 2019-04-24 000000m 22:52:26 - Overview

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Name (Institute + Shorttitle)The Darmstadt Noise Dataset 
Description (include details on usage, files and paper references)Lacking realistic ground truth data, image denoising techniques are traditionally evaluated on images corrupted by synthesized i. i. d. Gaussian noise. This is quite problematic, since noise in real photographs is not i. i. d. Gaussian and even seemingly minor details of the synthetic noise process, such as whether the noisy values are rounded to integers, can have a significant effect on the relative performance of methods.

Hence, we present a novel denoising benchmark, the Darmstadt Noise Dataset (DND). It consists of 50 pairs of real noisy images and corresponding ground truth images that were captured with consumer grade cameras of differing sensor sizes. For each pair, a reference image is taken with the base ISO level while the noisy image is taken with higher ISO and appropriately adjusted exposure time. The reference image undergoes a careful post-processing entailing small camera shift adjustment, linear intensity scaling and removal of low-frequency bias. The post-processed image serves as ground truth for our denoising benchmark. 
URL Linkhttps://noise.visinf.tu-darmstadt.de 
Files (#)50 
References (SKIPPED)
Category (SKIPPED) 
Tags (single words, spaced)denoising noise real photograph image synthetic quality benchmark 
Last Changed2019-04-24 
Turing (2.12+3.25=?) :-)