Median filtering enhanced self-evolving ghost imaging with adaptive illumination patterns

Single-pixel imaging (SPI) attracts lots of interest in X-ray, infrared, visible, and terahertz wave bands for the lower cost, wide-band compatibility, optical simplicity, robustness to noise, and fast sampling of single-pixel detection. Self-evolving ghost imaging (SEGI), as a new type of SPI, gives a new perspective by evolving the illumination patterns without postprocessing. Here, we improve the evolving efficiency of SEGI based on the continuity of the target, by applying a median image filter to the illumination patterns generated by the genetic algorithm. This method may help SEGI for practical applications such as real-time imaging, adaptive illumination, or human-robot interaction.