The LED luminaires are nowadays the mainstream of road lighting for the merit of durable, fast response, controllable,
energy saving, and environmental friendly. For the evaluation of highway with LED lightings, we have recently
developed on-site measurement of the photometric characteristics of lane and luminaire by luminance image,
illuminance and spectral illuminance distribution which be evaluated as uniformity, colorimetry and glare parameters
that were measured under the different height and spacing of the lampposts in the experimental field for expressway. We
applied the image luminance measurement device to achieve the on-site and real time road lighting evaluation especially
for the expressway. Some preliminary results were obtained from these experiments. These results will be applied to
developing the standards and specification for road lighting in expressway.
We have developed an image-based measurement method on UGR (unified glare rating) of interior lighting environment. A calibrated DSLR (digital single-lens reflex camera) with an ultra wide-angle lens was used to measure the luminance distribution, by which the corresponding parameters can be automatically calculated. A LED lighting was placed in a room and measured at various positions and directions to study the properties of UGR. The testing results are fitted with visual experiences and UGR principles. To further examine the results, a spectroradiometer and an illuminance meter were respectively used to measure the luminance and illuminance at the same position and orientation of the DSLR. The calculation of UGR by this image-based method may solve the problem of non-uniform luminance-distribution of LED lighting, and was studied on segmentation of the luminance graph for the calculations.
KEYWORDS: Video, Image quality, Human vision and color perception, Factor analysis, Image analysis, Image processing, Video processing, Image quality standards, Wavelets, Signal processing
Several estimative factors of image quality have been developed for approaching the human perception objectively1-3. We propose to take systematically distorted videos into the estimative factors and analyze the relationship between them. Several types of noise and noise weight were took into COSME standard video and verified the image quality estimative factors which were MSE (Mean Square Error), SSIM (Structural SIMilarity), CWSSIM (Complex Wavelet SSIM), PQR (Picture Quality Ratings) and DVQ (Digital Video Quality). The noise includes white noise, blur and luminance...etc. In the results, CWSSIM index has higher sensitivity at image structure and it could estimate the distorted videos which have the same noise type at the different levels. PQR is similar to CWSSIM, but the ratings of distribution were banded together; SSIM index divides the noise types into two groups and DVQ has linear relationship with MSE in the logarithmic scale.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.