System and method for deep learning-based color holographic microscopy

A system for performing color image reconstruction of a one or more super-resolved holographic image(s) of a sample comprising:

• a lensfree microscope device comprising a sample holder for holding the sample, a color image sensor, and one or more optical fiber(s) or cable(s) coupled to respective different colored light sources configured to simultaneously emit light at a plurality of wavelengths;
• at least one of a moveable stage or an array of light sources configured to obtain sub-pixel shifted lower resolution hologram intensity images of the sample;
• and
• a computing device having image processing software executed thereon, the image processing software comprising a trained deep neural network that is executed using one or more processors of the computing device, wherein the trained deep neural network is trained with a plurality of training images or image patches from a super-resolved hologram of the image of the sample and corresponding ground truth or target color images or image patches generated from hyperspectral imaging or brightfield microscopy, the trained deep neural network configured to receive one or more super-resolved holographic images of the sample generated by the image processing software from the sub-pixel shifted lower resolution hologram intensity images of the sample obtained with simultaneous illumination of the sample and output a reconstructed color image of the sample.