Point spread function (PSF) is a very important indicator of the imaging system; it can describe the filtering characteristics of the imaging system. The image is fuzzy when the PSF is not very well and vice versa. In the remote
sensing image process, the image could be restored by using the PSF of the image system to get a clearer picture. So, to measure the PSF of the system is very necessary. Usually we can use the knife edge method, line spread function (LSF) method and streak plate method to get the modulation transfer function (MTF), and then use the relationship of the
parameters to calculate the PSF of the system. In the knife edge method, the non-uniformity (NU) of the detector would
lead an unstable precision of the edge angle; using the streak plate could get a more stable MTF, but it is only at one
frequency point in one direction, so it is not very helpful to get a high-precision PSF. In this paper, we used the image of the point target directly and combined with the energy concentration to calculate the PSF. First we make a point matrix target board and make sure the point can image to a sub-pixel position at the detector array; then we use the center of
gravity to locate the point targets image to get the energy concentration; then we fusion the targets image together by
using the characteristics of sub-pixel and get a stable PSF of the system. Finally we use the simulation results to confirm
the accuracy of the method.
The performance of small and dim IR target detection is mostly affected by the signal to noise ratio(SNR) and signal to clutter ratio(SCR), for the MWIR especially LWIR array detector, because of the background radiation and the optical system radiation, the SCR cannot be unlimited increased by using a longer integral time, so the frame rate of the detector was mainly limited by the data readout time especially in a large-scale infrared detector, in this paper a new MWIR array detector with windowing technique was used to do the experiment, which can get a faster frame rate around the target by using the windowing mode, so the redundant information could be ignore, and the background subtraction was used to remove the fixed pattern noise and adjust the dynamic range of the target, then a local NUC(non uniformity correction) technique was proposed to improve the SCR of the target, the advantage between local NUC and global NUC was analyzed in detail, finally the multi local window frame accumulation was adopted to enhance the target further, and the SNR of the target was improved. The experiment showed the SCR of the target can improved from 1.3 to 36 at 30 frames accumulation, which make the target detection and tracking become very easily by using the new method.
It is always affected by the influence of limb atmosphere when the space-based remote sensing systems detect spatial targets using limb observation mode. In this paper, the characteristics of the limb atmosphere and the impact of limb atmosphere to target observation are theoretical modeled. Based on the model, we propose an algorithm to compute the vertical structure of atmosphere radiance through the image of limb atmosphere as well as the star image. Realization of atmosphere radiance under similar situation can then be computed based on inversion algorithm proposed in the paper. The stellar images of different areas including areas over Antarctic and Equator are captured by in-orbit space borne camera. The method of how to inverse from the gray image to atmosphere limb radiance in engineering applications is described in detail and statistical analysis of the result of inversion to limb atmosphere radiance is conducted whose trend is consistent with simulation result of MODTRAN which increases at lower altitude to a peak value then drop to zero slowly while there are two peaks in the statistical radiance distribution curves illustrating the polar light over Antarctic.
KEYWORDS: Sensors, Modulation transfer functions, Imaging systems, Analog electronics, CMOS sensors, Signal to noise ratio, Integrating spheres, Linear filtering, Spectral resolution, Aerospace engineering
With the requirements of high time resolution, high spatial and high spectral resolution development in geostationary orbit, photodetector pixel size has gradually become the bottleneck of the space exploration technology. Shanghai Institute of Technical Physics of Chinese Academy of Science has made a new breakthrough in CMOS image sensor area. The scale of its new CMOS image sensor achieves 2.5K×2.5K, and then use 24 detectors to achieve a detector whose scale is 150 million. The detector has been successfully imaging on the ground. In the application process, presents a systematic test and measurement methods to deal with the time noise, dark current, fixed pattern noise, MTF and other parameters of the detector. The test results are below. The MTF of the detector is 0.565 which is measured at 57.21/mm Nyquist frequency. The number of saturated electrons reaches 8.9×104. The total number of transient noise electrons is smaller than 16. The signal to noise ratio is 58.02dB. Through comprehensive analysis and measurement, it shows that the overall performance of the 2.5K×2.5K detector among the same types of products is in the leading position currently.
AS infrared CMOS Digital TDI (Time Delay and integrate) has a simple structure, excellent performance and flexible operation, it has been used in more and more applications. Because of the limitation of the Production process level, the plane array of the infrared detector has a large NU (non-uniformity) and a certain blind pixel rate. Both of the two will raise the noise and lead to the TDI works not very well. In this paper, for the impact of the system performance, the most important elements are analyzed, which are the NU of the optical system, the NU of the Plane array and the blind pixel in the Plane array. Here a reasonable algorithm which considers the background removal and the linear response model of the infrared detector is used to do the NUC (Non-uniformity correction) process, when the infrared detector array is used as a Digital TDI. In order to eliminate the impact of the blind pixel, the concept of surplus pixel method is introduced in, through the method, the SNR (signal to noise ratio) can be improved and the spatial and temporal resolution will not be changed. Finally we use a MWIR (Medium Ware Infrared) detector to do the experiment and the result proves the effectiveness of the method.
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.