High Dynamic Range Infrared Image Detail Enhancement And FPGA Implementation Technology

With the performance improvement and cost reduction of modern infrared imaging systems,they have been widely used in various fields.In order to improve the spatial and temperature resolution of infrared imaging systems,large-scale infrared focal plane arrays and high-bit AD converters are commonly used in modern infrared imaging systems,which greatly improves the dynamic range of infrared images,and make them contain a lot of details.However,due to the low dynamic range of traditional display devices,the images with high dynamic range from infrared imaging systems cannot be displayed directly on these display devices.In addition,infrared images have the characteristics of high background intensity and low contrast,and some details are submerged into background,which reduces the visual perception quality of images.In order to solve these two problems,dynamic range compression and detail enhancement algorithms of infrared images with high performance and low complexity are studied in this paper to provide high visual quality infrared images for practical applications.In this paper,the classic dynamic range compression and detail enhancement algorithms of infrared images are studied firstly.This paper focuses on algorithms on the BF&DRP framework,and several key technologies involved in related algorithms are introduced,such as bilateral filter,guided image filter,and local adaptive gamma correction.The reasons of halo effect and noise residual effect of guided image filter are analyzed in this paper.And weighted guided image filter,side window guided filter and anisotropic guided filter algorithms are introduced in detail.Then an improved guided filter algorithm combining first-order edge perception and side window anisotropic weighting is proposed.The simulation results of the proposed algorithm and the comparative analysis with existing algorithms have verified the effectiveness,superiority and robustness of the method proposed in this paper.In terms of dynamic range compression,based on the characteristics of the human visual system,an adaptive compression algorithm based on Sigmoid curve is used in this paper.And a new dynamic range compression and detail enhancement algorithm of infrared images which combines this compression algorithm and the improved guided filter is presented in this paper.Firstly,the improved guided filter is used to decompose the input high dynamic range infrared image into a base layer image and a detail layer image.Then the adaptive compression algorithm based on Sigmoid curve is used to compress the dynamic range of the base layer image.And a fixed gain factor is used to enhance the detail layer image.Finally,the processed base layer image and detail layer image are combined together to obtain the output low dynamic range infrared image.The subjective and objective evaluation metrics of the simulation results have shown that the algorithm can obtain high quality infrared images to meet the characteristics of visual perception.For real-time implementation of the infrared image enhancement algorithm,a hardware real-time processing system based on FPGA is designed in this paper.The infrared image enhancement system is introduced in detail.And the dynamic range compression and detail enhancement algorithm of infrared images proposed in this paper is implemented in this processing system.Analysis of system performance has shown that this algorithm can meet the requirements of real-time system and the output images have excellent visual performance.