A Spectral-based Color Vision Deficiency Model Compatible with Dichromacy and Anomalous Trichromacy

Abstract

This paper proposes a spectral-based CVD (Color Vision Deficiency) model compatible with both of dichromacy and anomalous trichromacy. The spectral projection model based on Matrix-R extracts the lost spectra as a difference in the fundamentals between the normal and the color deficient. The lost spectra are re-used for image daltonization by an optimal spectral shift to maximize the spectral visibility or minimize the visual gap from the normal. The model rationally improves the scene visibility after daltonization. The proposed algorithm is designed based on the original key ideas of 1) Acquisition of fundamental C*LMS (spectra visible to the normal) from sRGB camera image by a pseudo-inverse projection without expensive spectral image. 2) Foundation of projection matrix-RCVD onto dichromatic and anomalous trichromatic spectral spaces by combining the cone responses in the table by DeMarco&Pokorny& Smith. 3) Extraction of fundamental C*CVD (spectra visible to the dichromat or anomalous trichromat) by operating the matrix-RCVD on the fundamental C*LMS. 4) Introduction of complete OCS (Opponent-Color Space) to keep the perfect achromatic grayness in the opponent-color stage. 5) Estimation of lost spectra ΔC*CVD as the difference between visible spectra C*LMS to the normal and C*CVD to the dichromacy or anomalous trichromacy. 6) Color blindness correction (daltonization) by reviving the lost spectra ΔC*CVD with the optimal spectral shift into the visible waveband.