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Abstract
澳洲留学生电子科技研究论文 We propose a practical method of evaluating viewing angle characteristics, which comprises CIECAM02 based index and CIECAM02 based hardcopy set. The method is tested over visual experiments and its accuracy and applicability are successfully confirmed.

1.Introduction
The viewing angle characteristic has been one of the biggest disadvantages for LCD and rear-projection display over PDP or organic EL display and further improvement of viewing angle characteristics is strongly required. We proposed a new evaluation index which evaluates every change in brightness, saturation and hues while conventional is-contrast map evaluates only changes in brightness and its advantage over is-contrast map was successfully confirmed1. But, as the investigation has proceeded, we found that the index still has some difficulties with 1) accuracy (insufficient consideration of adaptation rate), 2) applicability (environment is limited), 3) evaluation of absolute image quality. To overcome these three difficulties, we examined the following investigations 1) employ appropriate adaptation rate, 2) employCIECAM02 image color difference, 3) bring hardcopy throughCIECAM02.

2. Appropriate adaptation rate for precise computation of evaluation index, adaptation state should be considered properly. When observer evaluates viewing angle characteristics, he observes displays from front and each angle in turn. In cases where white points in front and viewing angle image are different, it is hypothesized that adaptation states affected by both white points. Therefore, we examined the adaptation state through following experiment. Visual assessment was done over simulated images by using various adapting stimulus expressed as the inter-mediate point of the two, and appropriate adaptation rate (0.0 corresponds no adaptation and 1.0corresponds complete adaptation to white point in front image)was chosen (three kinds of pictures were used). Though this rate was set as 1.0 in our prior work, we found that it was reasonable to use 0.5 or less as the optimal adaptation rate without dependence on contents of pictures (Fig.1). Therefore, we use inter-mediate white point of front image and each viewing angle image when we calculate image color difference2.

3. CIECAM02 image color difference
The index is extended so as to be used not only in dark environment but also in bright environment where observers often watch display. Though CIELAB and CIELUV color spaces which provide uniform color differences are well-established and have been widely used as color spaces, those color spaces have some limitation such as assuming complete adaptation to illuminatntand incorporating no background or surround dependency.CIECAM02, the latest color appearance model from CIE, is an extension of basic chromatic adaptation model, where the adaptation effects to the environment are included. Hence, we applied CIECAM02 image color difference to predict the viewing angle characteristics which depend on viewing condition. In using the CIECAM02, we can derive appearance attributes of Lightness (J), Chrome(C), Hue (h). The CIECAM02 attributes are converted to the rectangular color appearance space coordinates Jack (=C coos (h)), by (=C sin (h)), and Hue (H) is computed by the use of following equation:
6. References
[1] K. Miyazaki, M. Yamada, Y. Mitsumori, M.本论文由英语论文网提供整理，提供论文代写，英语论文代写，代写论文，代写英语论文，代写留学生论文，代写英文论文，留学生论文代写相关核心关键词搜索。