Abstract | ||
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In this paper, we present a three-stage method for the estimation of the color of the illuminant in RAW images. The first stage uses a convolutional neural network that has been specially designed to produce multiple local estimates of the illuminant. The second stage, given the local estimates, determines the number of illuminants in the scene. Finally, local illuminant estimates are refined by n... |
Year | DOI | Venue |
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2015 | 10.1109/TIP.2017.2713044 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
Image color analysis,Estimation,Lighting,Training,Neural networks,Training data,Color | Training set,Computer vision,Color constancy,Data set,Pattern recognition,Convolutional neural network,Software,Artificial intelligence,Standard illuminant,Artificial neural network,Mathematics | Journal |
Volume | Issue | ISSN |
26 | 9 | 1057-7149 |
Citations | PageRank | References |
19 | 0.70 | 37 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Simone Bianco | 1 | 226 | 24.48 |
Claudio Cusano | 2 | 373 | 23.05 |
Raimondo Schettini | 3 | 1476 | 154.06 |