This tool transforms three intensity, hue, and saturation (IHS; sometimes HSI or HIS) raster images into three equivalent multispectral images corresponding with the red, green, and blue channels of an RGB composite. Intensity refers to the brightness of a color, hue is related to the dominant wavelength of light and is perceived as color, and saturation is the purity of the color (Koutsias et al., 2000). There are numerous algorithms for performing a red-green-blue (RGB) to IHS transformation. This tool uses the transformation described by Haydn (1982). Note that, based on this transformation, the input IHS values must follow the ranges:

0 < I < 1

0 < H < 2PI

0 < S < 1

The output red, green, and blue images will have values ranging from 0 to 255. The user must specify the names of the intensity, hue, and saturation images (intensity, hue, saturation). These images will generally be created using the rgb_to_ihs tool. The user must also specify the names of the output red, green, and blue images (red, green, blue). Image enhancements, such as contrast stretching, are often performed on the individual IHS components, which are then inverse transformed back in RGB components using this tool. The output RGB components can then be used to create an improved color composite image.

References

Haydn, R., Dalke, G.W. and Henkel, J. (1982) Application of the IHS color transform to the processing of multisensor data and image enhancement. Proc. of the Inter- national Symposium on Remote Sensing of Arid and Semiarid Lands, Cairo, 599-616.

Koutsias, N., Karteris, M., and Chuvico, E. (2000). The use of intensity-hue-saturation transformation of Landsat-5 Thematic Mapper data for burned land mapping. Photogrammetric Engineering and Remote Sensing, 66(7), 829-840.

See Also

rgb_to_ihs, balance_contrast_enhancement, direct_decorrelation_stretch

Function Signature

def ihs_to_rgb(self, intensity: Raster, hue: Raster, saturation: Raster) -> Tuple[Raster, Raster, Raster]: ...

Project Links

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