数码打样机小色差样张色差评价研究  

Research on Small Color-difference Evaluation of Digital Proofing Machine

作　　者：李文育[1,2] 张二虎[1] 刘宏昭[1] 

机构地区：[1]西安理工大学,西安710048 [2]陕西科技大学,西安710021

出　　处：《机械科学与技术》2013年第6期928-931,936,共5页Mechanical Science and Technology for Aerospace Engineering

基　　金：陕西省科技发展计划基金项目(2008K07-20)资助

摘　　要：针对目前数码打样机小色差样张ΔE76色差评价方法与视觉评价差异大的问题,提出了基于视觉特性的色差评价方法。首先设计了用于数码打样机用的小色差样张;然后采用感知法对数码打样机输出的小色差样张进行视觉评价,并将人眼恰能识别的色差利用ΔE76、ΔE94、ΔEcmc、ΔE00和ΔIm色差评价模型进行客观评价;最后采用均方根误差(RMSE)、性能评价因子(PF/3)、样品决定系数(R2)等参数,获得各色差评价模型相对视觉评价色差的预测性能。结果表明:与视觉评价最为一致的是ΔE00和ΔIm,与视觉评价差别最大的是ΔE76。与ΔE00色差评价模型相比,ΔIm色差评价模型不需要复杂的系数修正,计算简单,更适合作为数码打样机的色差评价模型在生产中应用。In order to solve the problem of the significant difference between AE76 and visual evaluation for small colordifference proofs of digital proofing machine, new evaluation methods have been put forward in this paper based on visual characteristics. First, small colordifference proofs are designed in this experiment for digital proo fing machine. Then, a visual perceptibility assessment method is applied on small colordifference proofs, and the justnoticeabledifferences were evaluated with the model of AE76, AE94, AE AEoo and AIm. The measured data were appraised using color rootmeansquared errors （ RMSE ） , performance evaluation factors （ PF/3 ） , sample decisive coefficients （R2） in order to obtain their prediction performance. The results show that the AE00 and AIm are closer to the subjective color difference, and the AE76 is the worst one. Benefited from its simple calculation method, the AIR method is better than other models as the colordifference evaluation model of digital proofing ma chine for production.

关 键 词：数码打样机 小色差样张 视觉评价 色差模型 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]