Illumination spectrum recovery
AssigneeCommonwealth Scientific and Industrial Research Organisation
InventorsNariman Habili, Jeremy Oorloff
Life of this patent
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Abstract
This disclosure concerns processing of electronic images, such as hyperspectral or multispectral images. In particular, this disclosure provides methods, software and computer systems for estimating an illumination spectrum of a digital image. A processor applies a neural network to the digital image by calculating three-dimensional convolutions in one or more convolutional layers of the neural network. The three-dimensional convolutions comprise a convolution along a spectral dimension. The processor then evaluates an output layer, connected to the one or more convolutional layers in the neural network. The output layer has multiple output values that each provide an intensity value for a respective band of the illumination spectrum of the digital image.
Claims18
A method for determining an illumination spectrum in a digital image, wherein the digital image is a hyperspectral image, the method comprising:
- applying a neural network to the digital image by:
- calculating three-dimensional convolutions in one or more convolutional layers of the neural network, the three-dimensional convolutions comprising a convolution along a spectral dimension, and each of the one or more convolutional layers comprises a convolution filter having a depth, a height and a width, wherein the depth of the convolution filter is greater than the height of the convolution filter and greater than the width of the convolution filter;
- and
- evaluating an output layer, connected to the one or more convolutional layers in the neural network, the output layer having multiple output values that each provide an intensity value for a respective band of the illumination spectrum of the digital image.
A computer system for determining an illumination spectrum in a digital image, wherein the digital image is a hyperspectral image, the computer system comprising a processor configured to apply a neural network to the digital image by:
- calculating three-dimensional convolutions in one or more convolutional layers of the neural network, the three-dimensional convolutions comprising a convolution along a spectral dimension, and each of the one or more convolutional layers comprises a convolution filter having a depth, a height and a width, wherein the depth of the convolution filter is greater than the height of the convolution filter and greater than the width of the convolution filter;
- and
- evaluating an output layer, connected to the one or more convolutional layers in the neural network, the output layer having multiple output values that each provide an intensity value for a respective band of the illumination spectrum of the digital image.
Dependencies are inferred from the claim text.