Abstract

Images in red–green–blue (RGB) color space need to be transformed to other color spaces for image processing or analysis. For example, the well-known hue-saturation-intensity (HSI) color space, which separates hue from saturation and intensity and is similar to the color perception of humans, can aid many computer vision applications. For high-dimensional images, such as multispectral or hyperspectral images, transformation images to a color space that can separate hue from saturation and intensity would be useful; however, the related works are limited. Some methods could interpret a set of high-dimensional images to hue, saturation, and intensity, but these methods need to reduce the dimension of original images to three images and then map them to the trichromatic color space of RGB. Generally, dimension reduction could cause loss or distortion of original data, and, therefore, the transformed color spaces could not be suitable for material classification in critical conditions. This paper describes a method that can transform high-dimensional images to a color space called hyper-hue-saturation-intensity (HHSI), which is analogous to HSI in high dimensions. The transformation does not need dimension reduction, and, therefore, it can preserve the original information. Experimental results indicate that the hyper-hue is independent of saturation and intensity and it is more suitable for material classification of proximal or remote sensing images captured in a natural environment where illumination usually cannot be controlled.

© 2017 Optical Society of America

Enhancing spatio-chromatic representation with more-than-three color coding for image description

Ivet Rafegas, Javier Vazquez-Corral, Robert Benavente, Maria Vanrell, and Susana Alvarez
J. Opt. Soc. Am. A 34(5) 827-837 (2017)

Dimensionality of color space in natural images

Antoni Buades, Jose-Luis Lisani, and Jean-Michel Morel
J. Opt. Soc. Am. A 28(2) 203-209 (2011)

How to deal with color in super resolution reconstruction of images

Rui Gong, Yi Wang, Yilin Cai, and Xiaopeng Shao
Opt. Express 25(10) 11144-11156 (2017)

Local receptive field constrained stacked sparse autoencoder for classification of hyperspectral images

Xiaoqing Wan and Chunhui Zhao
J. Opt. Soc. Am. A 34(6) 1011-1020 (2017)

Are Gaussian spectra a viable perceptual assumption in color appearance?

Yoko Mizokami and Michael A. Webster
J. Opt. Soc. Am. A 29(2) A10-A18 (2012)