研究目的
To propose a super-resolution infrared imaging method using time-varying coded mask based on focal plane coding and compressed sensing theory to improve infrared imaging quality.
研究成果
The proposed super-resolution infrared imaging method based on time-varying focal plane coding can obtain high quality images by using low resolution detector array. It significantly improves image quality compared with conventional imaging mode without coded mask. The method is promising for the practical design of new type of high resolution infrared imaging systems.
研究不足
The practical exposure time and the Signal to Noise Ratio (SNR) in the case of non-steady objects are not addressed in this study.
1：Experimental Design and Method Selection:
The method involves setting a coded mask on the focal plane of the optical system and using time-varying control coding strategy to sample the same scene repeatedly. The super-resolution image is reconstructed by sparse optimization algorithm.
2：Sample Selection and Data Sources:
A tank image of 512 × 512 pixels is taken as an original scene.
3：List of Experimental Equipment and Materials:
A 32 × 32 detector array is used to sample the original scene, with each detector element covering 16 × 16 pixels of the original scene.
4：Experimental Procedures and Operational Workflow:
The original scene is sampled with different compressed measurement coefficients (r) and coded mask resolutions (m). The reconstructed images are evaluated using PSNR and MTF.
5：Data Analysis Methods:
The quality of the reconstructed images is quantitatively evaluated using PSNR and MTF.
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