Multispectral Image Invariant to Illumination Colour, Strength, and Shading

We present here a method that makes use of multispectral image data and generates a novel "photometric-invariant multispectral image" for this type of data. For RGB, an invariant image has been constructed independent of the colour and intensity of the illuminant and of shading. To generate this image either a set of calibration images is required, or entropy information taken from a single image can be used to develop the parameters necessary to produce the invariant. Nonetheless, generating an invariant image remains a complex and error-prone task for RGB image data. For multispectral images, we show that photometric-invariant image formation is in essence greatly simplified. One of the requirements for forming an invariant is the necessity of narrowband-sensor sensors. Here this is the case, and we show that with the simple knowledge of peak sensor wavelengths we can generate a high-D multispectral invariant. The PSNR is shown to be high between the respective invariant multispectral features for multispectral images taken under different illumination conditions, showing lighting invariance for a per-pixel measure; and the s-CIELAB error measure shows that the colour error between the 3-D colour images used to visualize the output invariant high-D data is also small.