Application of an improved regularized super resolution reconstruction method in infrared detection system

3rd International Symposium on Resource Exploration and Environmental Science

生态环境科学

Xie, Qi^1 ; Zhang, Yufeng^1 ; Ru, Lina^2 ; Kang, Chenlong^1 ; Luo, Hongfei^1

Ordnance NCO Academy, Army Engineering University of PLA, Wuhan, China^1

Wuhan University of Engineering Science, Wuhan, China^2

关键词: Infrared detection;    Markov Random Fields;    Noise suppression;    Reconstructed image;    Reconstruction process;    Regularized method;    Super resolution reconstruction;    Superresolution methods;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/300/2/022091/pdf
DOI  :  10.1088/1755-1315/300/2/022091

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Super resolution reconstruction is a feasible technique to improve the image resolution without changing the existing infrared detection equipment. The original image usually contains noise, the traditional regularized super resolution method has the contradiction between restraining noise diffusion and protecting image details in the process of image reconstruction. In order to reduce the loss of reconstructed image information caused by noise suppression in the reconstruction process, this paper studied the reason of noise diffusion in original sequence image through image reconstruction model, proposed a method based on Lee's regularized method using Huber Markov random field as prior model in image reconstruction process, Experiment results show that the proposed method improved the images obtained by the infrared detection system, is superior to traditional method and Lee method in subjective visual and objective indicators, can meet the practical detection requirements.