Abstract:On the basis of the author''s existing work and thought, the splitting photon model is further analyzed and discussed. The relationship between the total quantity (e.g. absorbance, reflectivity and transmittance) on the sense of assemblage or integrity and the corresponding quantities of single photons (e.g. absorption fraction, reflection fraction and transmission fraction) is given. The splitting photon model can be used to explain the optical phenomena such as reflection, diffraction, interference and so on. On the basis of the Monte Carlo method and the splitting photon model, the optical phenomena such as reflection, diffraction and interference can be simulated by computer. The idea of simulation algorithm is presented.

Abstract:To solve the problem that traditional infrared target detection and recognition methods always blindly carry out time-consuming searching for a whole image in their processing processes, an infrared sea surface target detection and recognition method based on visual attention mechanism and level set method is proposed. Firstly, the salient regions in an original image are searched and are denoted in terms of winner points. Then, on the basis of the salient regions captured, the level set function is initialized automatically and the evolution process is forced to go forward towards the expected target contour until its final equilibrium. Finally, for the input data obtained at a long distance (or at a short distance), the detection results are given (the recognition results based on moment invariants and neutral network framework). The validity of the proposed method is verified in the experiment made on the real infrared sea surface targets.

Abstract:In the color fusion images obtained by traditional color transfer algorithms, the color of the target is similar to that of the background and the target becomes faded. To solve this problem, an infrared and low-level-light image color fusion method based on color contrast enhancement is proposed. Firstly, the infrared image and the low-level-light image are fused in color. Then, the color transfer is implemented on the color reference image and the pseudocolor fusion image. Secondly, the Otsu segmentation method is used to extract the target information in the low-level-light image and hence the target area image is obtained. Finally, the target area in the HIS color space is used to adjust the HIS component of the fusion image obtained through color transfer. The final fused image is obtained. The experimental result shows that the color fusion image obtained by this method has the features of high target-background contrast, rich detail and better color. It can help human eyes detect and identify targets quickly.

Abstract:At present, infrared scene simulation has become an important method for the design and evaluation of infrared imaging guided weapons. On the basis of analyzing the principle of infrared imaging, a real-time infrared scene simulation method of ground tank targets based on OpenGL is proposed and a software for simulation program is compiled. Firstly, a visible light scene is built by OpenGL and the temperature field model of the scene is built by the ANSYS software. Secondly, considering the attenuation effect of the atmosphere between the model and the viewpoint, an atmospheric attenuation model is established by the Modtran software. Finally, the intensity of infrared radiation from each part of the model to the surface of the detector is quantified in gray-level so as to realize the real-time rendering of the visible light scene and obtain the corresponding infrared simulation image. The simulation results show that the system can improve the real-time performance and convenience in the calculation of the infrared radiation distribution of targets and can generate infrared images in different wavebands under different atmospheric environment conditions in real time.

Abstract:Memory Effect (ME) noise is a stripe noise which occurs in infrared opto-mechnical scanning images. It is particularly obvious for the scene with a bright-dark mutation in the image. It may affect the visual effectiveness of the image seriously. The traditional ME noise removal methods usually use a system impulse response function to build a restoration filter for restoring images. The disadvantage is that there should be an accuracy impulse response function. In view of the disadvantages of traditional methods, a new ME noise removal algorithm is proposed. In the algorithm, the radiation information of image self is used, a detection template is used to traverse the whole scene image so as to detect ME noise and an iterative method is used to remove the detected noise. Finally, the IRMSS images from CBERS01 satellite are selected to make experiment. The experimental results show that this method can remove ME noise effectively so that it can improve the radiation quality of images.

Abstract:Since the factors such as low signal intensity and complicated environment may cause the spectrum to be cluttered and cause the wave peak to be not obvious, it is difficult for infrared remote sensing to detect precursor chemical vapor accurately. Even the basic digital filtering algorithm is used, the problem can not be solved. For this reason, a filtering algorithm based on Kalman/Wiener superimposion is proposed. By using this algorithm to preprocess spectral signals, the qualitative detection accuracy in subsequent wave peak match can be improved effectively. The experimental data collected are verified on the basis of the improved algorithm. The result shows that compared with other filtering algorithms, the improved algorithm can filter interference signals effectively and can identify characteristic peaks accurately.

Abstract:From the definition of spatial resolution, it is pointed out that the numerical aperture of an objective lens and the wavelength of light are the main factors for determining the spatial resolution of optical instruments. The principle that the spatial resolution affects the measurement accuracy of the junction temperature of semiconductor devices is given. Microscopic infrared temperature detection is conducted on GaN HEMTs at different spatial resolution. The temperature measurement results obtained at lower spatial resolution are less accurate than those obtained at high spatial resolution. This shows that insufficient spatial resolution may result in less accurate temperature measurement results.

Abstract:A hyperspectral technology was utilized to estimate the Equivalent Water Thickness (EWT) of apple leaves in a rapid and nondestructive way, which could provide a reference for the early warning of growth and drought of apple trees. Taking the leaves of Red Fuji apple trees in Qixia, Yantai, Shandong Province as experimental materials, the correlation among EWT, original spectral reflectance and 13 kinds of transformation spectral reflectance was analyzed on the basis of the spectral reflectance of apple tree leaves and the calculation of their EWT. After the sensitive wavelengths were screened out, an estimation model of the EWT of apple tree leaves based on support vector regression was established. Among the 13 kinds of spectral transformation, 3 kinds of transformation such as the first derivative (FDR), the first derivative of the square root (FD(SqrtR)) and the first derivative of the logarithm of the reciprocal (FD[Lg(1/R)]) had better correlation. The sensitive wavelengths for estimating the EWT of apple tree leaves were determined. On the basis of the support vector regression, a mode for quantitatively estimating the blade EWT was established. The coefficient of determination R2 of the validation set reached 0.8147 and the relative percent deviation (RPD) reached 2.2671. The results showed that the model had better estimation ability and the support vector regression was more suitable to estimate the EWT of apple tree leaves. This method provided technical support for the quantitative estimation of the growth status of apples by hyperspectral techniques.