16,046 research outputs found
Convolutional Mean: A Simple Convolutional Neural Network for Illuminant Estimation
We present Convolutional Mean (CM) – a simple and fast convolutional neural network for illuminant estimation. Our proposed method only requires a small neural network model (1.1K parameters) and a 48 × 32 thumbnail input image. Our unoptimized Python implementation takes 1 ms/image, which is arguably 3-3750× faster than the current leading solutions with similar accuracy. Using two public datasets, we show that our proposed light-weight method offers accuracy comparable to the current leading methods’ (which consist of thousands/millions of parameters) across several measures
Color homography
We show the surprising result that colors across a change in viewing
condition (changing light color, shading and camera) are related by a
homography. Our homography color correction application delivers improved color
fidelity compared with the linear least-square.Comment: Accepted by Progress in Colour Studies 201
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