Research On Infrared Weak Targets Imaging Under Strong Background And Information Processing Technology

Infrared detection has the advantages of the around-the-clock monitoring and high concealment,which makes it play a significant role in marine meteorological forecast and sea-surface targets observation.The sensitivity of the long-wave infrared detection system quantifies the discernibility of the system towards the change of the targets’ radiation characteristics.Marine infrared detection system can detect the main factors,such as the emissivity and temperature difference,whether it is emissivity or temperature difference,the sea texture contrast is low,which means that the demand of the infrared detection system’s sensitivity is particularly high;different sea surface texture represents different sea conditions.The study of sea surface texture is helpful for sea surface modeling,sea condition analysis and sea surface target detection.Aiming at the high-sensitivity requirements and the texture research of sea-surface background,the main contents and innovations of this paper are as follows:First,the distribution and variation of ocean-surface temperature,the infrared detection system’s selection of waveband,methods of image formation and requirements of sensitivity are researched and analyzed.According to the requirement,a long-wave infrared detection’s information-acquisition sub-system is designed,which mainly includes low-noise analog-signal-acquisition circuits,FPGA control circuits,data preprocessing and transmission and so on.In the push-sweep imaging,the multi-sampling integration and digital TDI technique between the adjacent dwell time are used to improve the system noise equivalent temperature difference(NETD).One of the innovations in this paper is that analysis and design infrared detection system to achieve high sensitivity,on the condition that the temperature of the surface blackbody is 300 K and the integration time is 250 us,the NETD of the system is 21.98 mK,which is equivalent to the sensitivity of the detector itself.The system sensitivity can be decreased to less than 10 mK by multiple sampling integration and digital TDI.Second,preprocess the infrared images in view of the laboratory data,which includes blind detection and compensation,calibration-based and scene-based infrared images’ non-uniformity correction.Based on the pre-processing,the column noise location and compensation method are realized.The method can effectively improve the visual effect of the image,and it has a crucial role in the detection of the sea surface and the extraction of the texture feature.In this paper,the rows strip noise removal method based on wavelet transforming,spatial filtering,mean and standard deviation estimation is studied.The algorithm is based on the airspace,frequency domain,wavelet transform and so on.The algorithm is easy to implement without affecting the non-band region image information.Third,the method of hierarchical decomposition,enhancement and merging of infrared images is proposed.The method can be better in preserving the small texture information than the histogram equalization enhancement method,and it will not cause image area too light or too dark.To achieve the calm sea surface infrared detection,the image’s high and low frequency is separated.The high frame rate system can effectively remove the noise,completing the target detection and positioning.In the multi-clutter sea surface,the visual significance model is applied to the clutter suppression.The second innovation in this paper is that implement the clutter image target detection algorithm based on the visual significance.The algorithm achieves single-frame image target detection without being affected by the filter parameters.The effectiveness of the algorithm is verified by simulation,and the detection rate is 98.5%.Fourth,the infrared texture image has been studied.The study can effectively extract the triangular texture feature,effectively eliminate the influence of the background,and extract the small texture of the low contrast of the ocean.The ocean vortex image is enhanced while the equivalent processing and the morphological filtering are applied to the ocean vortex image.The image texture is described by the gray-level co-occurrence matrix,and the texture is classified according to the statistical information such as texture contrast,gray correlation,energy and so on.The main direction and texture feature of texture image are determined by Fourier transform.Characterization and classification of texture images have been realized by local binary pattern(LBP).The third innovation in this paper is that characterization of ocean texture images have been researched.The study meets the requirement of high-sensitivity infrared detection under the complex ocean background.The preprocessing of ocean infrared image and the extraction and classification of marine texture features play a significant role in the study of marine texture and ocean-target observation.