KEYWORDS: Signal to noise ratio, Imaging systems, Space telescopes, Mathematical modeling, Photonics systems, Astronomy, Radiometry, Interference (communication), Signal processing, Detection and tracking algorithms
Photon imaging system (PIS) is widely applied to astronomy observing, deep space exploration. To investigate the
system performance for space application, the process that target radiance converting to photons is presented. In this
processes, radiometry theory and astronomy units are used. Then a mathematical physical model for the imaging system
is used to calculate the system SNR. In the model, the system dark noise and the signal enhancement process are derived
as mathematical equations. The performance of the detection algorithm is also introduced to predict the PIS range
performance of the probability of detection and correct localization and the probability of false alarm based on SNR. At
last, the actual PIS range performance for space application is discussed and valuable data for space telescopes design and
deep space exploration also are provided.
In order to analyze the invalidation of the Semiconductor Device and IC, we proposed a novel digital thermal microscope
based on the uncooled focal plane detector. We give the operating principle, system's construction and the mathematical
mode of noise equivalent temperature difference (NETD). Based on the mathematical model, some measures were taken
to increase the system temperature resolution. Furthermore we proposed an adaptive nonuniformity correction algorithm
for the UFPA. The software for the thermal microscope is provided based on Visual C++. Results of real thermal image
experiments have shown that the digital thermal microscope is designed successfully and achieves good performance.
Thus it will become an effective means for invalidation Analysis. This method is a novel and unique contribution to field
of semiconductor device and IC invalidation analysis.
A scene-based nonuiformity correction occurred in the operation of recursive reconstruction for high resolution extracted
from subpixel microscan imaging (SMI) sequence are presented and analyzed. The reconstruction algorithm in terms of
block-by-block method recursive from the prescient boundary to centre in uniform 2×2 SMI, is updated to the
two-dimensional focus plane array (FPA) considering the arbitrary scan translation not equivalent to the accurate
halfpixel. In this paper, the focus is concentrated to the nonuniform SMI model with fixed pattern noise (FPN), which
corrupts the image by the gain and offset from the individual cell-detector. Then, we firstly demonstrate that once our
backward recursive reconstruction implements to the undersampled sequence with FPN, the dramatic impact to the
majority pixels is the elimination of the offset due to the quits efficiency by inverse iterative function in each 2×2 region
belonging to the high resolution lattice. The final achievement is the nonuiformity correction (NUC) synchronously
concomitant with the higher resolution, so our method fully takes account of the potential information of the scanned
inter-frames. Application of proposed algorithm to the simulated SMI procedure has the obvious superiority, including
the much better image quality indexes from the cleaned FPN, time-consumed saving within one scan period (4 frames),
no requirements of statistical assumption so as to the avoidance of ghost artifact, and the inter-frames adaptive property.
A photon imaging system (PIS), which consists of object lens, micro-channel plate (MCP), photomultiplier tube, relay
lens, CCD camera and image acquisition system is recently constructed. The dark noise of the whole imaging system has
been studied by statistical analysis method. The hypothesis tests method is used to analyze statistical parameters of dark
noise. In this test, the Chi-square goodness-of-fit test method is employed to determine which distribution the acquired
image information is fit for. Subsequently, the section estimation is used to confirm threshold for spatial denoising
process. In order to overcome the effects of the non-uniformity for PIS, we propose a new method to analyze above
processes. In this method the image acquired by PIS was divided into many segments, their statistical characters have
been studied respectively and the statistical parameters of the noise for the different segments are analyzed based on
above method. For the aim of analyzing above acquired statistical parameters and obtaining the relationship in terms of
the different operating conditions of the system, several experiments have been implemented and experiment results also
be presented.
For the subpixel micro-scanning imaging, we propose the reconstruction algorithm based on neither interpolation nor
super-resolution idea but one of the block-by-block method recursive from the boundary to centre when additional
narrowband boundary view-field diaphragm whose radiation is known a prior. The aim of the predicted boundary value
is to add the conditions for solving the ununiqueness ill-problem to the inverse transition matrix from the destructed
process. For the non-uniform scan factor, the improved algorithm associated with certain non-uniform motion variables
is proposed. Additionally, attention is focused on the case of unknown subpixel motion, when the reconstructed images
are blurred by motion parameter modulation and neighbouring point aliasing because the value of micro-motion is not
the correct one. Unlike other methods that the image registration is accomplished before multi-frame restoration from
undersampled sequences frame by frame, in this paper, 2-D motion vector is estimated in single frame just from the blur
character of reconstructed grids. We demonstrate that once the estimated motion approaches to the real one, square
summation of all pixels over the unmatched image approximately descends to the minimum. The matching track based
on recursive Newton secant approaching is optimized for high matching speed and precision by different strategies,
including matching region hunting, matching direction choosing and convergence prejudgement. All iterative step
lengths with respect to motion parameters are substituted by the suitable values derived from the statistic process and one
or multi-secant solution. The simulations demonstrate the feasibility of the matching algorithm and the obvious
resolution enhancement compared to the direct oversampling image.
This paper concentrates on images formation simulation under low light level condition (10-6-3lx) and photon
limited condition (<10-6lx). In the first part, we introduce the main characteristics and features of low light level images
and system entire noise and simulate a deblurred image intensified by photon imaging system recently constructed under
low light level condition. The influence of scene luminance and photon imaging system optical errors on the simulation
is introduced. Then the system entire noise is appended to low light level images by a novel noise analysis and
generation method based on experimental study method. The second part of this paper deals with simulation of photon
images. Because of randomicity of photon images, roulette wheel selection is utilized to confirm the grey level of
stochastic signal photon image and noise photon image is generated by poissson stochastic process pixel by pixel. The
final photon image is acquired by synthesizing the two images. The simulation presented in this paper provides an
economical and convenient method to investigate the detection ability of photon imaging system and image
reconstruction algorithm under low light level condition and photon limited condition.
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