The　image　color　recorded　in　a　computer　vision　system　depends　on　three　factors:　the　physical　content　of　the　scene,　the　illumination　on　the　scene,　and　the　characteristics　of　the　camera.　The　goal　of　computational　color　correction　is　to　reset　the　intensities　of　the　color　channels　in　digital　images,　and　express　the　scene　colors　canonically.　In　the　color　correction　method　based　on　spectral　reflectance　reproduction,　the　finite-dimensional　linear-model　is　an　effective　way　to　condense　spectral　reflectance.　Since　there　are　only　three　channels　for　each　pixel　in　digital　images,　color　correction　based　on　spectral　reflectance　reproduction　using　the　finite-dimensional　model　with　three　dimensions　is　needed.　In　the　definite　gamut,　the　spectral　reflectance　curves　are　analyzed　using　the　finite-dimensional　model.　It　is　shown　that　reflectance　generated　by　three　basis　functions　which　is　capturing　99.13%　of　the　overall　variance,　provides　good　approximations　to　the　measured　spectral　reflectance.　Together　with　the　measured　spectral　power　distribution　of　the　illumination　and　the　estimated　spectral　responses　of　the　camera,　the　quantum　catches　are　calculated.　Errors　caused　by　approximation　of　the　finite-dimensional　model　are　relatively　small,　which　shows　that　color　correction　based　on　the　finite-dimensional　linear-　model　has　feasibility　to　some　extent.　©　2008　IEEE.