Metrics for Evaluating Spectral Matches: A Quantitative Comparison

نویسنده

  • J. A. Stephen Viggiano
چکیده

Several of the spectral match metrics considered by Imai, et al., are compared for a large number of non-metameric pairs of spectra in order to assess how accurately they track human perception as predicted by CIELAB (i.e., the extent to which the metric will exhibit a proportional relationship with CIELAB total color difference), and how precisely they do so (i.e., the relative compactness of the distribution of a metric for spectral pairs which differ by a given level of CIELAB total color difference). Both properties are important attributes of a spectral match metric. Of particular importance in optimization problems is the precision as the total color difference becomes small. We found that among the metrics considered, only unweighted RMS and Viggiano’s Spectral Comparison Index provided precision for both large and small color differences. The Viggiano Spectral Comparison Index had the closest correlation to human perception, and, for the non-metameric spectral pairs examined in this study, assumed values close to 2,6 times that of CIELAB ∆E*. The paper includes a definition of non-metameric spectra, and describes a method for generating them, which include variations in Lightness, Hue, and Chroma.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Comparative Study of Metrics for Spectral Match Quality

The selection of metrics for spectral matches is fundamental to MVSI (multi-channel visible-spectrum imaging) otherwise known as spectral imaging. The metrics used for spectral matches can impact everything from the selection of the filters used for multi-channel capture to the evaluation of the spectral estimation. However, there is, as yet, no consensus on which metric should be applied for s...

متن کامل

Representing Spectral data using LabPQR color space in comparison to PCA method

In many applications of color technology such as spectral color reproduction it is of interest to represent the spectral data with lower dimensions than spectral space’s dimensions. It is more than half of a century that Principal Component Analysis PCA method has been applied to find the number of independent basis vectors of spectral dataset and representing spectral reflectance with lower di...

متن کامل

Quality Metrics for Spectral Estimation

The quantitative assessment of the spectral estimation quality in multispectral imaging systems is an active field of research. The design and optimization of multispectral imaging systems are very dependent on how the cost function is selected. Several spectral estimation metrics have been used depending on the attribute it is intended to measure: visual matching, correlation of spectral curve...

متن کامل

Metrics and Evaluation Tools for Patient Engagement in Healthcare Organization- and System-Level Decision-Making: A Systematic Review

Background Patient, public, consumer, and community (P2C2) engagement in organization-, community-, and systemlevel healthcare decision-making is increasing globally, but its formal evaluation remains challenging. To define a taxonomy of possible P2C2 engagement metrics and compare existing evaluation tools against this taxonomy, we conducted a systematic review.   Methods A broad search strate...

متن کامل

Quantifying Vocal Mimicry in the Greater Racket-Tailed Drongo: A Comparison of Automated Methods and Human Assessment

Objective identification and description of mimicked calls is a primary component of any study on avian vocal mimicry but few studies have adopted a quantitative approach. We used spectral feature representations commonly used in human speech analysis in combination with various distance metrics to distinguish between mimicked and non-mimicked calls of the greater racket-tailed drongo, Dicrurus...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004