UV spectral radiation detecting and visible observation telescope is designed by the coaxial optical. In order to decrease due to the incident light polarization effect, and improve the detection precision, polarizer need to be used in the light path. Four pieces of quartz of high Precision UV radiation depolarizer retarder stack together is placed in front of Seya namioka dispersion unit. The coherent detection principle of modulation of light signal and the reference signal multiplied processing, increase the phase sensitive detector can be adjustment function, ensure the UV spectral radiation detection stability. A lock-in amplifier is used in the electrical system to advance the accuracy of measurement. To ensure the precision measurement detected, the phase-sensitive detector function can be adjustable. the output value is not more than 10mV before each measurement, so it can be ensured that the stability of the measured radiation spectrum is less than 1 percent.
A modified spectrometer with tandem gratings that exhibits high spectral resolution and imaging quality for solar observation, monitoring, and understanding of coastal ocean processes is presented in this study. Spectral broadband anastigmatic imaging condition, spectral resolution, and initial optical structure are obtained based on geometric aberration theory. Compared with conventional tandem gratings spectrometers, this modified design permits flexibility in selecting gratings. A detailed discussion of the optical design and optical performance of an ultraviolet spectrometer with tandem gratings is also included to explain the advantage of oblique incidence for spectral broadband.
The microvasculature network of retina plays an important role in the study and diagnosis of retinal diseases (age-related
macular degeneration and diabetic retinopathy for example). Although it is possible to noninvasively acquire
high-resolution retinal images with modern retinal imaging technologies, non-uniform illumination, the low contrast of
thin vessels and the background noises all make it difficult for diagnosis. In this paper, we introduce a novel retinal
vessel extraction algorithm based on gradient vector flow and matched filtering to segment retinal vessels with different
likelihood. Firstly, we use isotropic Gaussian kernel and adaptive histogram equalization to smooth and enhance the
retinal images respectively. Secondly, a multi-scale matched filtering method is adopted to extract the retinal vessels.
Then, the gradient vector flow algorithm is introduced to locate the edge of the retinal vessels. Finally, we combine the
results of matched filtering method and gradient vector flow algorithm to extract the vessels at different likelihood levels.
The experiments demonstrate that our algorithm is efficient and the intensities of vessel images exactly represent the
likelihood of the vessels.