Compressive Sampling Approach for Image Acquisition with Lensless Endoscope
This is an incremental improvement for in vivo cellular imaging with lensless endoscopes.
The paper tackled the slow calibration and scanning in lensless endoscopes by proposing a compressive sampling method using random illumination patterns, achieving experiments on synthetic data with compression rates from 10% to 100% of the field of view.
The lensless endoscope is a promising device designed to image tissues in vivo at the cellular scale. The traditional acquisition setup consists in raster scanning during which the focused light beam from the optical fiber illuminates sequentially each pixel of the field of view (FOV). The calibration step to focus the beam and the sampling scheme both take time. In this preliminary work, we propose a scanning method based on compressive sampling theory. The method does not rely on a focused beam but rather on the random illumination patterns generated by the single-mode fibers. Experiments are performed on synthetic data for different compression rates (from 10 to 100% of the FOV).