## 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](https://en.wikipedia.org/wiki/Lab_color_space). 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](https://en.wikipedia.org/wiki/Lab_color_space) 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](https://en.wikipedia.org/wiki/HSL_and_HSV). 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](https://en.wikipedia.org/wiki/HSL_and_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 ```lua image.display{image=image.y2jet(torch.linspace(1,10,10)), zoom=50} ```