A first signal photon unit method (FSPU) was proposed in this paper which is suitable for photon-counting imaging application with low signal level and severe noise. The method exploits the different statistics of signal detections and noise detections that signal detections would cluster while noise detections tend to be equally distributed to distinguish signal from noise. For each spatial pixel, laser illumination would not stop until the first signal photon unit or the first n detections that cluster within ε range is discovered where n and ε is a preset parameter to describe what kind of cluster we wish to identify. The number of pulses to obtain this first signal photon unit is a random variable and it contains the intensity information. Depth and intensity images are reconstructed through the mean time of FSPU and maximum likelihood estimation from the number of emitted pulses respectively. Simulation verifies its feasibility even when signal to noise ratio is well below 0dB.
In the use of image sensors such as CCD, CMOS and so on, the noise caused by thermal dark signal will influence the imaging results to a certain extent. Dark current noise exists in every photoelectric devices and it is directly related to the temperature. So it’s a principle way that cool the image sensors’ temperature to suppress the dark current noise. This article presents a kind of TEC cooling package integrated with four stages TEC, a heat sink and an insulating cavity, to meet the requirement of image sensors’ refrigeration. Theoretical analysis of this cooling package was done from the view of heat transfer. The modeling and thermal simulated analysis are performed by finite element simulation analysis software ANSYS Icepak, comparing the experimental results in the conditions of different ambient temperature, different heat load and vacuumizing or filling the cavity.
For the disadvantage of traditional target detection methods with low detection rate and difficulties in distinguishing the small temperature difference and camouflage targets, this paper presents a kind of visible polarization image fusion method using non-subsampled Shearlets transform. Firstly, we obtain four polarization status images by multi-detector camera, where the direction of polarization angle is 0° 、45°、90°、135° separately. The Stokes vectors are calculated by polarization status images. Then, the extracted target polarization feature images and light intensity image are decomposed into several sub frequency bands by NSST with fine multi-scale decomposition characteristics. Meanwhile, the fusion coefficients are determined based on high-frequency energy window and low-frequency mean in the frequency domain. At last, the final fusion image is obtained after NSST inverse transform and target enhancement. Experimental results illustrate that the proposed approach could obtain better fusion images with rich details, high contrast, highlighting the polarization characteristic of the target to improve the ability of scene perception and target detection.
Although high dynamic range (HDR) images contain large amounts of information, they have weak texture and low contrast. What's more, these images are difficult to be reproduced on low dynamic range displaying mediums. If much more information is to be acquired when these images are displayed on PCs, some specific transforms, such as compressing the dynamic range, enhancing the portions of little difference in original contrast and highlighting the texture details on the premise of keeping the parts of large contrast, are needed. To this ends, a multi-scale guided filter enhancement algorithm which derives from the single-scale guided filter based on the analysis of non-physical model is proposed in this paper. Firstly, this algorithm decomposes the original HDR images into base image and detail images of different scales, and then it adaptively selects a transform function which acts on the enhanced detail images and original images. By comparing the treatment effects of HDR images and low dynamic range (LDR) images of different scene features, it proves that this algorithm, on the basis of maintaining the hierarchy and texture details of images, not only improves the contrast and enhances the details of images, but also adjusts the dynamic range well. Thus, it is much suitable for human observation or analytical processing of machines.
KEYWORDS: Interference (communication), Signal processing, LIDAR, Wavelets, Signal to noise ratio, Wavelet transforms, Sensors, Signal detection, Signal analyzers, Denoising
As the ladar bathymetry is affected by many factors, its echoed signal contains a lot kinds of noises. There are the
interference noise of laser, the clutter noise, the water-reflected noise, the underwater scattered noise, the electric noise and the synoptic disturbance noise after analyzing the echoed signal. Consequently, how to remove noise from the signal and how to accurately extract the useful distance information has the direct bearing on the effect of the ladar bathymetry. On the basis of kinds of noises and the features of the noises, this paper puts forward a echoed signal de-noising method by the way of wavelet decomposition and threshold processing. To begin with, it introduces some kinds of noise. Then, it talks over how to treat with the echoed signal according to the heterogeneities of the signal and the noise. The processing of echoed signal de-noising of ladar bathymetry makes it clear that this method can not only actively suppress the noise, but also effectively abstract the useful signal.
A new, simple and compact experimental laser scanning imaging system is introduced for underwater imaging, and the
characteristics of the system are analyzed in this paper. The system consists of the illuminator, optical scanning system,
optical receiving system, narrow band filters, high-sensitivity gated image sensor, synchronous control and data
acquisition system and power supply and cooling system. The illuminator is a lump-pumped, Q-switched, frequency
doubled Nd:YAG pulsed laser operating at 532 nm with a frequency of 50 Hz. The receiver is a self-made gated intensified
charge coupled device (ICCD). As a result, gated super Gen-II image intensifier and PAL format charge-coupled device
(CCD) camera are assembled to meet the requirements. The coupling gated ICCD has a sensitivity of approximated 10-5lx,
and the minimum gate width can reach to 40 ns. And a set of scanning structure which only uses one mirror is used in the
experimental system. In addition, the performance parameters are listed. Finally, the detection capabilities of the imaging
system are theoretically analyzed in typical seawater. The analysis indicates that the detection depth of the system can
reach to 16 m in the clear seawater.
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