Research On High Dynamic Infrared Imaging Technology

Infrared imaging technology is widely used in various fields and plays an important role in military and civilian livelihoods.However,due to the deficiencies in the manufacturing process of the infrared detectors,infrared images have the disadvantages of low contrast and blurred details.In order to improve the dynamic range of infrared images,current infrared detectors mostly use high-bit-width ADCs,and the resulting infrared images contain richer scene and detailed information.In order to match the human eye observation or display device display,the high dynamic range infrared image needs to be processed by bit-width compression technology.However,the compressed image still has the disadvantages of low ratio and lack of detailed information.Therefore,this article focuses on the contrast enhancement and detail enhancement algorithms,and proposes two improved algorithms,and implements the hardware implementation of the two improved algorithms based on FPGA platform.This article first studies the histogram equalization algorithm,which can improve the contrast while compressing the high dynamic range infrared image.The common algorithms are simulated,and the advantages and disadvantages of the corresponding algorithms under the simulation conditions are analyzed.Aiming at the defects of the common algorithms,this paper combines local histogram equalization and dualplatform histogram equalization,and proposes a local histogram equalization algorithm based on dual-platform thresholds.Compared with other commonly used algorithms,the algorithm in this paper has a further contrast enhancement effect.Then,in view of the lack of image detail loss after the infrared image is blurred and the bit width compression and contrast enhancement,the detail enhancement algorithm is discussed,and the image noise reduction and detail enhancement algorithm combining guided filtering and Gaussian filtering is proposed,which has achieved good results.Then,the hardware circuit with FPGA as the core is designed,the SOPC framework is built through Qsys,and the parameters are configured with Nios II as the control center.Finally,the algorithm is implemented in hardware.Through real-time observation,the contrast and details of the imaging results of the infrared system are improved.