Pan sharpening uses spatial information in the high-resolution grayscale band and color information in the multispectral bands to create a high-resolution color image, essentially increasing the resolution of the color information in the data set to match that of the panchromatic band.
One common class of algorithms for pansharpening is called “component substitution,”[2] which usually involves the following steps: Common color-space transformation used for pan sharpening are HSI (hue-saturation-intensity), and YCbCr.
The same steps can also be performed using wavelet decomposition or PCA and replacing the first component with the pan band.
As a result, the spectral characteristics of the raw pansharpened color image may not exactly match those of the corresponding low-resolution RGB image, resulting in altered color tones.
This has resulted in the development of many algorithms that attempt to reduce this spectral distortion and to produce visually pleasing images.