英语翻译Statistical Significance of the DifferencesBy applying t

英语翻译
Statistical Significance of the Differences
By applying the U-test,27 we have checked when our main
parameter S2% has significantly different values in the four
previous datasets.This nonparametric test was preferred,
because no assumptions about the underlying distributions
are necessary.The formulas being statistically different at a
90% confidence level are connected by asterisks in Fig.7.
Among the main conclusions from Fig.7,it can be noted
that CIE94 is significantly different than CIELAB for all the
datasets (and the same can be stated for CMC and BFD for three of the four wide datasets analyzed in this figure).In
addition,we also observe that CIE94 and CMC are not
significantly different for any of our datasets at a 90%
confidence level (and even for any of the experimental
works considered in the group of classical literature17–20).
BFD is significantly different than CIE94,except for the
Luo and Rigg ellipses,21 probably because most of the
ellipses in this dataset were used for the development of
BFD.It should also be noted that CIELAB and CIELUV are
significantly different for the two datasets having ellipsoids,
but not for those having ellipses.For future developments
and testing of color-difference formulas,the use of pairs of
samples with an appropriate tridimensional distribution
around each center (such as made,for example,with those
used in the design of the RIT-DuPont experiment22),should
be emphasized.24
CONCLUSION
In summary,the last few years have,in our opinion,seen
significant improvements in the prediction of the magnitude
of perceived color-differences,by the use of several
CIELAB-based formulas,in particular CIE94.Of course,
much more research needs to be done within this topic,for
example,by analyzing the influence of specific parametric
factors,such as those affecting the optimal weighting function
for lightness differences.14 In any case,we believe that
the current structure of the CIE94 formula will be useful,at
least in the near future,without disregarding that the current
use of the CIELAB space as the starting point could be
surpassed by advances in the knowledge concerning color
appearance and the physiology of our visual system.

统计学意义的差异
采用u检验,27日检查时,我们的主要
参数二％有显着不同的价值观的四个
以往的数据集.这是首选的非参数检验,
因为没有任何假设的基本分布
是必要的.公式是不同的统计
90 ％置信水平连接的星图.7 .
其中的主要结论从图.7 ,可以指出
这是很大的不同CIE94色差比所有的
数据集（同样可以说为中央军委的BFD三四个广泛数据分析,这个数字） .印第安纳州
此外,我们也观察到,CIE94和中央军委不
显着性差异我们提供的任何数据在90 ％
置信水平（甚至任何实验
工作组审议的古典literature17 - 20 ） .
明显不同的BFD比CIE94 ,除了
罗和里格省略号21日,可能是因为大部分
省略号在这一数据被用于发展
的BFD .还应当指出的是色差和CIELUV
明显不同的两个数据集有椭球,
但不适用于那些有省略号.为今后的发展
和测试色差公式,使用双
样品进行适当的立体分布
每个中心（如作出的,例如,对于那些
用于设计的RIT公司,杜邦公司experiment22 ） ,应
被emphasized.24
结论
总之,过去几年,我们认为,阅读
显着改善预测的严重性
知觉颜色的差异,利用几个
色差的计算公式,特别是CIE94 .当然,
更多的研究需要做的这个主题,为
例如,通过分析具体的影响参数
因素,如那些影响到最优加权函数
为明度differences.14在任何情况下,我们认为,
目前结构的CIE94公式将是有益的,在
至少在不久的将来,同时不忽视,目前的
利用色差空间为出发点可以
超过的进步,知识的颜色
外观和生理的影响我们的视觉系统.