Fusion of infrared (IR) and visible sensor images is the widely applied. The registration is the basis for sensor fusion and fusion methods are very sensitive to the level of registration accuracy. However, the different imaging systems of the both lead to quite different image characteristics in a same scene and significant misalignment due to differences in field of view, lens distortion and other camera characteristics. So that, the registering accurately the both of sensor images is very challenging. A method to improve the accuracy of image registration is proposed in this paper. The method is based a self-designed long-wave IR/visible dual-band imaging system for capturing simultaneously both of images, which is not only with synchronous focusing and optical registration as much as possible, but also with a sliding potentiometer that record the voltage corresponding to the focusing distance. At first, an affine transformation of the registration at several different distances is acquired with two calibration board images captured self-designed calibration board by the dual-band imaging system. Then, the affine transformation matrices corresponding to the several finite distance are interpolated to obtain more affine transformation matrices within a certain distance, and an accurate look-up table is established. Last, when the dual-band imaging system is working, the current focal length is read out according to the sliding potentiometer in the system, and then the corresponding affine transformation matrix is searched for image registration. The proposed method is evaluated by comparing the deviation of the corresponding feature point coordinates on both of calibration board images before and after registration. Experimental results show that the proposed method can improve the registration accuracy of IR and visible images at different distances.
KEYWORDS: Infrared detectors, Imaging systems, Signal detection, Infrared imaging, Sensors, Analog electronics, Infrared sensors, Image processing, Infrared radiation, Control systems
The long wave infrared imaging systems have been used widely in military and civil fields. With the rapid development of semiconductor technology, new architectures of embedded systems are emerging and developing towards the direction of lower power consumption, higher integration and stronger performance. The traditional hardware circuit design scheme of infrared detector adopts single-FPGA solutions or discrete DSP+FPGA solutions. The above two schemes have disadvantages such as hard algorithm transplantation, hard serial processing and too complex hardware circuit. In this paper, a hardware circuit for a long-wave infrared detector based on Xilinx Zynq with SOPC architecture is developed, which includes a detector driving circuit, a detector temperature control circuit, an analog-to-digital conversion circuit, a signal processing circuit, and a digital signal output circuit. When the system is working, the signals generated by the detector are input into Xilinx Zynq after an analog-to-digital conversion operation. Then, after being cached by DDR3 chip, non-uniformity correction, dynamic compression and image enhancement are completed in Xilinx Zynq. Finally, the infrared video is transmitted to the remote PC through the network for real-time display through UDP protocol of gigabit Ethernet. The software on the PC supports functions such as screenshot, video recording and log query. Experiment as results show that a uncooled long-wave infrared detector with the resolution 640×512 are driven by the proposed scheme, which has advantages of sufficient data bandwidth, easy serial processing and simple process of memory control. The system designed by this scheme has good imaging effect and strong extensibility.
Infrared imaging systems have been widely used in military and civil fields. However, the degradation of imaging quality is constantly affected by stripe noises. The traditional mean filtering, median filtering, Gaussian filtering, Wiener filtering and other algorithms have dependence on different noise images, and the image edge is blurred by denoising. The popular bilateral filter takes a lot of calculation due to a two-dimension way and floating point spatial proximity factor. In this paper, an infrared sequence image denoising method based on multi-frame averaging and improved bilateral filtering is introduced. An improved bilateral filter with an integer spatial proximity factor is designed, which is realized by one dimension filtering in horizontal and vertical directions. First, basal stripe in each frame image is removed by two-point correction, and the improved bilateral filter is used to smooth the noise and protect the edge of the image at the same time. Second, random noise is further removed by averaging multi-frame with a set of 25 images. The experimental results show that the proposed denoising method can effectively remove the noise and better maintain the edge structural information of the image.
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