Super-resolution algorithm applied to images acquired at millimeter wave frequency in single pixel and computational ghost imaging configurations

The lack of low cost, high-resolution two-dimensional imaging detectors and the expensiveness of the measurements make millimeter wave imaging challenging. Single detector configurations are promising to solve data acquisition problem in millimeter wave imaging. In this study, millimeter wave imaging in transmission mode is done with single pixel imaging and computational ghost imaging configurations. In order to reduce the number of measurements in each configuration, Compressed Sensing architecture is used. To increase the image resolution, software-based super-resolution is applied. To the best of our knowledge, this is first study comparing the computational ghost imaging with single pixel imaging, besides software-based super-resolution method is applied to the real world millimeter wave images. It is seen that super-resolution increases the quality in both configurations while computational ghost imaging has better quality compared to single pixel imaging in millimeter waves.