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Color Space Conversions

This section includes functions for performing conversions between different color spaces.

[res] image.rgb2lab([dst,] src)

Converts a src RGB image to Lab. If dst is provided, it is used to store the output image. Otherwise, returns a new res Tensor.

[res] image.lab2rgb([dst,] src)

Converts a src Lab image to RGB. If dst is provided, it is used to store the output image. Otherwise, returns a new res Tensor.

[res] image.rgb2yuv([dst,] src)

Converts a RGB image to YUV. If dst is provided, it is used to store the output image. Otherwise, returns a new res Tensor.

[res] image.yuv2rgb([dst,] src)

Converts a YUV image to RGB. If dst is provided, it is used to store the output image. Otherwise, returns a new res Tensor.

[res] image.rgb2y([dst,] src)

Converts a RGB image to Y (discard U and V). If dst is provided, it is used to store the output image. Otherwise, returns a new res Tensor.

[res] image.rgb2hsl([dst,] src)

Converts a RGB image to HSL. If dst is provided, it is used to store the output image. Otherwise, returns a new res Tensor.

[res] image.hsl2rgb([dst,] src)

Converts a HSL image to RGB. If dst is provided, it is used to store the output image. Otherwise, returns a new res Tensor.

[res] image.rgb2hsv([dst,] src)

Converts a RGB image to HSV. If dst is provided, it is used to store the output image. Otherwise, returns a new res Tensor.

[res] image.hsv2rgb([dst,] src)

Converts a HSV image to RGB. If dst is provided, it is used to store the output image. Otherwise, returns a new res Tensor.

[res] image.rgb2nrgb([dst,] src)

Converts an RGB image to normalized-RGB.

[res] image.y2jet([dst,] src)

Converts a L-levels (1 to L) greyscale image into a L-levels jet heat-map. If dst is provided, it is used to store the output image. Otherwise, returns a new res Tensor.

This is particulary helpful for understanding the magnitude of the values of a matrix, or easily spot peaks in scalar field (like probability densities over a 2D area). For example, you can run it as

image.display{image=image.y2jet(torch.linspace(1,10,10)), zoom=50}