Hyperspectral imaging has become a common technique in many different applications, enabling accurate identification of materials based on their optical properties; however, it requires complex and expensive technical implementation. A less expensive way to produce spectral data, spectral estimation, suffers from complex mathematics and limited accuracy. We introduce a novel, to the best of our knowledge, method where spectral reflectance curves can be reconstructed from the measured camera responses without complex mathematics. We have simulated the method with seven non-negative broadband transmission filters extracted from Munsell color data through principal component analysis and used sensitivity and noise levels characteristic of the Retiga 4000DC 12-bit monochrome camera. The method is sensitive to noise but produces sufficient reproduction accuracy even with six filters.