P-36: A New Viewing-Angle Evaluation Method for LCDs with Image Color Difference

2005 ◽  
Vol 36 (1) ◽  
pp. 406 ◽  
Author(s):  
Keiichi Miyazaki ◽  
Makoto Yamada ◽  
Yutaro Mitsumori ◽  
Isao Fujiwara ◽  
Masamitsu Ishida
Keyword(s):  
Evaluation Method ◽  
Color Difference ◽  
Viewing Angle

Research on Chromaticity Characterization Methods of the Ink Trapping

2012 ◽  
Vol 262 ◽  
pp. 113-118 ◽  
Author(s):  
Jiang Hao Liu ◽  
Shao Hong Gao
Keyword(s):  
Evaluation Method ◽  
Density Measurement ◽  
Color Difference ◽  
Characterization Methods ◽  
Advantages And Disadvantages ◽  
Density Evaluation ◽  
Color Printing ◽  
Color Value ◽  
The Ideal ◽  
Trapping Effects

The practical applied formula are based on the density measurement in ink trapping characterization methods, but the density measurement is more suitable for detecting single color printing effect. Due to the defects of the testing equipment, the density measurement is not suitable for the evaluation of ink trapping. Chromaticity evaluation method bases on the color difference between the sample color values and the ideal color values to evaluate ink trapping effects, which can characterize better on the ink trapping effects. Research results showed that the density evaluation method has many deficiencies, and Neugebauer equations predict on the chroma evaluation method doesn’t reach an enough precise to get the ideal value about the secondary overprinting, while the color value which is measured by spectroscopic measurement by experimental methods can be used as the ideal color value of the chromaticity evaluation method. Study on the comparison between density evaluation method and chroma evaluation method of ink trapping, the relative conclusions about advantages and disadvantages of different ink trapping characterization methods will be summarized.

41.4: Subjective Image Quality of Viewing Angle beyond Color Difference Metric in FPD

2013 ◽  
Vol 44 (1) ◽  
pp. 574-577
Author(s):  
Chao-Hua Wen ◽  
Yan-Yu Lin ◽  
Pin-Chou Huang ◽  
Ting-Wei Hsu ◽  
Hsin-Hong Chen ◽  
...  
Keyword(s):  
Image Quality ◽  
Color Difference ◽  
Viewing Angle ◽  
Subjective Image Quality

scholarly journals A Color Consistency Processing Method for HY-1C Images of Antarctica

2020 ◽  
Vol 12 (7) ◽  
pp. 1143 ◽  
Author(s):  
Zhijiang Li ◽  
Haonan Zhu ◽  
Chunxia Zhou ◽  
Liqin Cao ◽  
Yanfei Zhong ◽  
...  
Keyword(s):  
Quantitative Evaluation ◽  
Coastal Zone ◽  
Evaluation Method ◽  
Low Frequency ◽  
Color Difference ◽  
Atmospheric Environment ◽  
Global Ocean ◽  
Consistency Results ◽  
New Processing ◽  
Processing Framework

The HY-1C satellite, as part of China’s optical satellite constellation for global ocean monitoring, monitors the ocean and coastal environment by the three broad visible bands of the Coastal Zone Imager (CZI) instrument. However, as a result of the sensor instrument noise, the atmospheric environment during imaging, and the shooting angle, the satellite images often show uneven illumination and inconsistent color between neighboring images. In this paper, according to the characteristics of the HY-1C CZI instrument, we propose a color consistency processing framework for coastal zone images of Antarctica. First of all, the high-frequency and low-frequency information of the image is separated by a statistical filter with simple clustering. The uneven lighting is then replaced by artificial lighting, which is globally uniform. Finally, the color difference between images is corrected by a color transfer method. In order to evaluate the color consistency results quantitatively, a new quantitative evaluation method is proposed. The experimental results for the coastal zone images of Antarctica show that the new processing framework can effectively eliminate the unevenness in the lighting and color. The mosaic results show a good performance in consistent lighting and tones, and the lack of visible mosaic lines proves the effectiveness of the proposed method. The quantitative evaluation analysis confirms the superiority of the proposed method over the Wallis method.

Evaluation Method of Fabric Color Difference Based on Saliency Algorithm and CIELAB Space

2018 ◽  
Vol 55 (5) ◽  
pp. 053301
Author(s):  
孟秀萍 Meng Xiuping ◽  
苏工兵 Su Gongbing ◽  
吴奇明 Wu Qiming ◽  
袁浪佳 Yuan Langjia
Keyword(s):  
Evaluation Method ◽  
Color Difference

Viewing-angle evaluation method for LCDs with gray-scale images

1993 ◽  
Vol 1 (4) ◽  
pp. 405 ◽  
Author(s):  
Junko Hirata ◽  
Yuzo Hisatake ◽  
Masahito Ishikawa ◽  
Masato Shoji ◽  
Yasuharu Tanaka ◽  
...  
Keyword(s):  
Evaluation Method ◽  
Viewing Angle ◽  
Gray Scale

Research on the Color-Difference Evaluation of Food Package Printing Matter Based on the Human Visual Characteristics

2013 ◽  
Vol 469 ◽  
pp. 278-281 ◽  
Author(s):  
Zhi Jian Li ◽  
Qing Jun Meng
Keyword(s):  
Evaluation Method ◽  
Color Difference ◽  
Reference Image ◽  
Target Image ◽  
Food Package ◽  
Difference Formula ◽  
Visual Characteristics ◽  
Opposite Color ◽  
Space Image ◽  
Human Visual Characteristics

In order to improve for the inadequacy of traditional evaluation methods, this paper researched a kind of color-difference evaluation method for the food package printing matter based on human visual characteristics. Research method is as follow: the reference image and the target image were transformed to the opposite color space, and were dealt with the human eye Contrast Sensitive Function (CSF) spatial filter. The modified three opposite color component of images were transformed into the CIE XYZ space image after CSF spatial filtering processed; finally the image was transformed to the CIELAB space image. The color-difference of the target image was calculated according to color-difference formula. The color-difference result of image is the calculation result with human visual characteristics filtering processed; it combines subjective evaluation with objective evaluation. The research could provide practical and effective evaluation method for the field of food package printing matter.

Viewing-angle evaluation method of color shift for LCDs with gray-scale images

1994 ◽  
Vol 2 (4) ◽  
pp. 169 ◽  
Author(s):  
Masahito Ishikawa ◽  
Makiko Sato ◽  
Yuzo Hisatake ◽  
Hitoshi Hatoh
Keyword(s):  
Evaluation Method ◽  
Viewing Angle ◽  
Gray Scale ◽  
Color Shift

Evaluation method for imaging plate resolution by means of phase contrast transfer function

1995 ◽  
Vol 53 ◽  
pp. 662-663 ◽  
Author(s):  
T. Oikawa ◽  
H. Kosugi ◽  
F. Hosokawa ◽  
D. Shindo ◽  
M. Kersker
Keyword(s):  
Transfer Function ◽  
Phase Contrast ◽  
Evaluation Method ◽  
Amorphous Film ◽  
Imaging Plate ◽  
X Rays ◽  
Special Shape ◽  
Contrast Transfer Function ◽  
Contrast Image ◽  
Specimen Shape

Evaluation of the resolution of the Imaging Plate (IP) has been attempted by some methods. An evaluation method for IP resolution, which is not influenced by hard X-rays at higher accelerating voltages, was proposed previously by the present authors. This method, however, requires truoblesome experimental preperations partly because specially synthesized hematite was used as a specimen, and partly because a special shape of the specimen was used as a standard image. In this paper, a convenient evaluation method which is not infuenced by the specimen shape and image direction, is newly proposed. In this method, phase contrast images of thin amorphous film are used.Several diffraction rings are obtained by the Fourier transformation of a phase contrast image of thin amorphous film, taken at a large under focus. The rings show the spatial-frequency spectrum corresponding to the phase contrast transfer function (PCTF). The envelope function is obtained by connecting the peak intensities of the rings. The evelope function is offten used for evaluation of the instrument, because the function shows the performance of the electron microscope (EM).

Combining Values

2002 ◽  
Vol 7 (2) ◽  
pp. 1-4, 12 ◽  
Author(s):  
Christopher R. Brigham
Keyword(s):  
Lower Extremity ◽  
Upper Extremity ◽  
Evaluation Method ◽  
Proximal Phalanx ◽  
Common Error ◽  
The Third ◽  
Whole Person ◽  
Impairment Ratings ◽  
Upper Extremity Impairment ◽  
The Individual

Abstract To account for the effects of multiple impairments, evaluating physicians must provide a summary value that combines multiple impairments so the whole person impairment is equal to or less than the sum of all the individual impairment values. A common error is to add values that should be combined and typically results in an inflated rating. The Combined Values Chart in the AMA Guides to the Evaluation of Permanent Impairment, Fifth Edition, includes instructions that guide physicians about combining impairment ratings. For example, impairment values within a region generally are combined and converted to a whole person permanent impairment before combination with the results from other regions (exceptions include certain impairments of the spine and extremities). When they combine three or more values, physicians should select and combine the two lowest values; this value is combined with the third value to yield the total value. Upper extremity impairment ratings are combined based on the principle that a second and each succeeding impairment applies not to the whole unit (eg, whole finger) but only to the part that remains (eg, proximal phalanx). Physicians who combine lower extremity impairments usually use only one evaluation method, but, if more than one method is used, the physician should use the Combined Values Chart.

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