Block-based compressed sensing for fast optic fiber bundle imaging with high spatial resolution

Abstract

The resolution of traditional fiber bundle imaging is usually limited by the density and the diameter of the fiber cores. To improve the resolution, compression sensing was introduced to resolve multiple pixels from a single fiber core, but current methods have the drawbacks of excessive sampling and long reconstruction time. In this paper, we present, what we believe to be, a novel block-based compressed sensing scheme for fast realization of high-resolution optic fiber bundle imaging. In this method, the target image is segmented into multiple small blocks, each of which covers the projection area of one fiber core. All block images are independently and simultaneously sampled and the intensities are recorded by a two-dimensional detector after they are collected and transmitted through corresponding fiber cores. Because the size of sampling patterns and the sampling numbers are greatly reduced, the reconstruction complexity and reconstruction time are also decreased. According to the simulation analysis, our method is 23 times faster than the current compressed sensing optical fiber imaging for reconstructing a fiber image of 128 × 128 pixels, while the sampling number is only 0.39%. Experiment results demonstrate that the method is also effective for reconstructing large target images and the number of sampling does not increase with the size of the image. Our finding may provide a new idea for high-resolution real-time imaging of fiber bundle endoscope.