Glaucoma was diagnosed or tracked by the intraocular pressure (IOP) generally because it is one of the physiology
parameters that are associated with glaucoma. But measurement of IOP is not easy and consistence under different
measure conditions. An infrared videopupillography is apparatus to monitor the pupil size in an attempt to bypass the
direct IOP measurement. This paper propose an infrared videopupillography to monitoring the pupil size of different
light stimulus in dark room. The portable infrared videopupillography contains a camera, a beam splitter, the visible-light
LEDs for stimulating the eyes, and the infrared LEDs for lighting the eyes. It is lighter and smaller than the present
product. It can modulate for different locations of different eyes, and can be mounted on any eyeglass frame. An analysis
program of pupil size can evaluate the pupil diameter by image correlation. In our experiments, the eye diameter curves
were not smooth and jagged. It caused by the light spots, lone eyelashes, and blink. In the future, we will improve the
analysis program of pupil size and seek the approach to solve the LED light spots. And we hope this infrared
videopupillography proposed in this paper can be a measuring platform to explore the relations between the different
diseases and pupil response.
The holographic data storage system (HDSS) is a page-oriented storage system with advantages of great capacity and
high speed. The page-oriented recording breaks the tradition of the optical storage of one-point recording. As the
signal image is retrieved from the storage material in the HDSS, various noises influences the image and then the
data retrieve will be difficultly from the image by using the thresholding method. For progressing on the thresholding
method, a recognition method, based on the structural similarity, is proposed to replace the thresholding method in
the HDSS. The recognition method is implemented that the image comparison between the receive image and
reference image is performed by the structural similarity method to find the most similar reference image to the
received image. In the experiment, by using recognition method, the bit error rate (BER) results in 26% decrease less
than using the thresholding method in the HDSS. Owing to some strong effects, such as non-uniform intensity and
strong speckle, still influencing on the received image, the recognition method is seemed to be slightly better than
thresholding method. In the future, the strong effects would be reduced to improve the quality of the receive image
and then the result of using the recognition method may be vastly better than the thresholding method.
KEYWORDS: Endoscopes, Light emitting diodes, Mirrors, Intestine, 3D image reconstruction, Monte Carlo methods, Geometrical optics, Light sources, LED lighting, Endoscopy
This paper is researching about the illumination system in ring field capsule endoscope. It is difficult to obtain the
uniform illumination on the observed object because the light intensity of LED will be changed along its angular
displacement and same as luminous intensity distribution curve. So we use the optical design software which is
Advanced Systems Analysis Program (ASAP) to build a photometric model for the optimal design of LED illumination
system in ring field capsule endoscope. In this paper, the optimal design of illumination uniformity in the ring field
capsule endoscope is from origin 0.128 up to optimum 0.603 and it would advance the image quality of ring field capsule
endoscope greatly.
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.