On Some Desired Properties of Data Augmentation by Illumination Simulation for Color Constancy (CROSBI ID 699747)
Prilog sa skupa u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Banić, Nikola ; Koščević, Karlo ; Subašić, Marko ; Lončarić Sven
engleski
On Some Desired Properties of Data Augmentation by Illumination Simulation for Color Constancy
Computational color constancy is used in almost all digital cameras to reduce the influence of scene illumination on object colors. Many of the highly accurate published illumination estimation methods use deep learning, which relies on large amounts of images with known ground-truth illuminations. Since the size of the appropriate publicly available training datasets is relatively small, data augmentation is often used also by simulating the appearance of a given image under another illumination. Still, there are practically no reports on any desired properties of such simulated images or on the limits of their usability. In this paper, several experiments for determining some of these properties are proposed and conducted by comparing the behavior of the simplest illumination estimation methods on images of the same scenes obtained under real illuminations and images obtained through data augmentation. The experimental results are presented and discussed.
color constancy ; data augmentation ; illumination estimation ; image enhancement ; white balancing
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Podaci o prilogu
27-38.
2020.
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objavljeno
10.5121/csit.2020.101903
Podaci o matičnoj publikaciji
Computer science and information technology
Wyld, David C.
AIRCC Publishing Corporation
2231-5403
Podaci o skupu
9th International Conference on Signal, Image Processing and Pattern Recognition (SPPR 2020)
predavanje
19.12.2020-20.12.2020
Sydney, Australija