Since the polarization image contains abundant information of the object, the detecting ability of imaging system would be improved via observing the polarization features of this object. On the basis of analysis to the polarization characteristics, the active polarized imaging method is introduced in this paper, and active polarized imaging platform is built. Through this system, 3 typical samples of aluminum, iron with yellow coating, iron with green coating are adopted to simulate different objects on the sea. By measuring the parameters of amplitude ratio P, phase retardation θ, and completely depolarized coefficient ωd on the platform, which stand for the surface property of the material, we can testify the accuracy of the idea. The experiments result shows that the measured P and θ values are consistent with Fresnel equations, while for ωd , the value of seawater differs from that of the other two coating samples dramatically. As a result, it is feasible to discriminate coating target on the sea by measuring the depolarization characteristics.
Proc. SPIE. 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition
KEYWORDS: Signal to noise ratio, Principal component analysis, Image processing, Video, Digital filtering, Interference (communication), Gaussian filters, Signal processing, Image filtering, Video processing
A de-noising method based on PCA (Principal Component Analysis) is proposed to suppress the noise of LLL (Low-Light Level) image. At first, the feasibility of de-noising with the algorithm of PCA is analyzed in detail. Since the image data is correlated in time and space, it is retained as principal component, while the noise is considered to be uncorrelated in both time and space and be removed as minor component. Then some LLL images is used in the experiment to confirm the proposed method. The sampling number of LLL image which can lead to the best de-noising effects is given. Some performance parameters are calculated and the results are analyzed in detail. To compare with the proposed method, some traditional de-noising algorithm are utilized to suppress noise of LLL images. Judging from the results, the proposed method has more significant effects of de-noising than the traditional algorithm. Theoretical analysis and experimental results show that the proposed method is reasonable and efficient.
Considering the complex features of public
places such as mass passenger flow, congestion
and disorder, it is hard to count the number of
passengers precisely. In this paper, a method of
passenger counting system is proposed based on
the range image. This system takes advantage of a
Kinect sensor to acquire the 3D depth information.
First of all, the range image is smoothed with Mean
Shift algorithm to direct every partial pixel toward the
maximal probability density enhanced. Therefore,
the smoothened range image can be better applied
to the subsequent image processing. Secondly, a
classical dynamic threshold segmentation method is
applied to segment the head regions, and the 3D
characteristics of heads are analyzed. They are
differentiated by pixel width, area and circle-like
shape, which efficiently surpass the limits of 2D
images. In addition, the self-adaptive multi-window
tracing method is applied for predicting possible
trajectories, speeds and positions of multi-windows,
in which we establish tracing chains of multiple
targets and lock the tracing targets precisely. This
method proves to be efficient for background noise
removal and environmental disturbance suppression
and can be applied for implementation of the
identifying and counting of heads in public places.
The staring imaging technique is one of the main research directions in the field of the opto-electronic imaging. Therefore, the analysis of imaging performance of staring imaging system is a key issue in the research work. It includes the following parameters, MTF, SNR, MRTD, distortion etc, among which MTF is one of the most important parameters in evaluating the performance of the detector and the system. In this paper, we report a thorough analysis on the characteristics of MTF from the spatial and frequency spectrum. This Fourier transform based analysis was performed on the dynamic imaging characteristics of staring imaging system. Furthermore, abundant experiments were made on the measurement of MTF of visible CCD and IRFPA, thereby the results was obtained for the performance analyzing of staring imaging system.
In the field of medical application, it is of great importance to
adopt digital image processing technique. Based on the
characteristics of medical image, we introduced the digital image
processing method to the X-ray imaging system, and developed a
high resolution x-ray medical sequential image acquisition and
processing system that employs image enhancer and CCD. This system
consists of three basic modules, namely sequential image
acquisition, data transfer and system control, and image
processing. Under the control of FPGA (Field Programmable Gate
Array), images acquired by the front-end circuit are transmitted
to a PC through high speed PCI bus, and then optimized by the
image processing program. The software kits, which include PCI
Device Driver and Image Processing Package, are developed with
Visual C++ Language based on Windows OS. In this paper, we present
a general introduction to the principle and the operating
procedure of X-ray Sequential Image Acquisition and Processing
System, with special emphasis on the key issues of the hardware
design. In addition, the context, principle, status quo and the
digitizing trend of X-ray Imaging are explained succinctly.
Finally, the preliminary experimental results are shown to
demonstrate that the system is capable of achieving high quality
X-ray sequential images.