Eliminating material dependency in spectra measurement via non-neighbouring band regression

A multispectral imaging system, after necessary calibration, can measure the spectral reflectances of colour samples accurately at a high spatial resolution. A limitation is that agreement of its measurements with those of a reference spectrophotometer is affected by the reflective characteristics of sample materials. The state-of-the-art methods aim to improve interinstrument agreement using the spectral values of neighbouring bands. However, it is observed that non-neighbouring bands are more effective in modelling interinstrument agreement. Inspired by this observation, the present paper proposes a method for eliminating material dependency by least-squares regression among non-neighbouring spectral bands. The fundamental issue of band selection is solved using a binary differential evolution algorithm. Experimental results confirm that the proposed method is effective in reflectance correction in terms of both spectral and colorimetric accuracy. The method is of practical application to multispectral imaging systems when measuring the spectral reflectances of colour samples with different materials.