Research on infrared super-resolution based on criterion of subjectivity and objectivity joint evaluation
Received:April 25, 2019  Revised:November 15, 2019  download
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Author NameAffiliationPostcode
SHAO Bao-Tai Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
University of Chinese Academy of Sciences, Beijing 100049, China
Key Laboratory of Intelligent Infrared Perception, Chinese Academy of Sciences, Shanghai 200083, China 
200083
TANG Xin-Yi Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
Key Laboratory of Intelligent Infrared Perception, Chinese Academy of Sciences, Shanghai 200083, China 
ZHANG Ning  
Abstract:In the application of infrared super-resolution imaging, it is actually necessary to improve the subjective visual effects of images. At present, most image super-resolution reconstruction methods based on deep learning are trained and optimized with objective evaluation index as loss function. The subjective evaluation methods are difficult to apply due to the difficulty of quantification. Therefore, this paper focuses on the correlation between subjective evaluation and quantifiable objective evaluation indexes, and finds that the characteristics of phase consistency are highly correlated with subjective evaluation results. Based on this, a loss function based on subjective and objective joint evaluation is designed and applied to the super-resolution reconstruction algorithm of infrared image. Experiments show that this method can improve the subjective visual effect of image while maintaining the objective evaluation score.
keywords:super-resolution reconstruction  infrared image  subjective and objective joint evaluation  loss function
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Copyright:《Journal of Infrared And Millimeter Waves》