Abstract
Single-pixel imaging uses a single-pixel detector, rather than a focal plane detector array, to image a scene. It provides advantages for applications such as multi-wavelength, three-dimensional imaging. However, low frame rates have been a major obstacle inhibiting the use of computational ghost imaging technique in wider applications since its invention one decade ago. To address this problem, a computational ghost imaging scheme, which utilizes an LED-based, high-speed illumination module is presented in this work. At 32 × 32 pixel resolution, the proof-of-principle system achieved continuous imaging with 1000 fps frame rate, approximately two orders larger than those of other existing ghost imaging systems. The proposed scheme provides a cost-effective and high-speed imaging technique for dynamic imaging applications.
Highlights
As an alternative to using a focal-plane detector array, single-pixel computational ghost imaging [1], an improved scheme of ghost imaging [2, 3] and closely related to single-pixel imaging [4,5,6], retrieves a two-dimensional image by recording only the total light intensities in each component of a spatial sampling basis, rather than capturing it with a pixelated array as in a digital camera
The approaches include using devices such as spatial light modulator (SLM) [1], and utilizing compressive sensing [15,16,17] to reduce the number of acquisitions that computational ghost imaging requires to reconstruct an image
We significantly improved the frame rate using a computational ghost imaging scheme based on a high-speed LED illumination module
Summary
As an alternative to using a focal-plane detector array, single-pixel computational ghost imaging [1], an improved scheme of ghost imaging [2, 3] and closely related to single-pixel imaging [4,5,6], retrieves a two-dimensional image by recording only the total light intensities in each component of a spatial sampling basis, rather than capturing it with a pixelated array as in a digital camera. The approaches include using devices such as spatial light modulator (SLM) [1], and utilizing compressive sensing [15,16,17] to reduce the number of acquisitions that computational ghost imaging requires to reconstruct an image. Compressive sensing does decrease the required number of acquisitions for each frame, the subsequent convex optimization procedure to reconstruct the image requires a computational overhead, which poses difficulties for real-time dynamic applications. With the help of the evolutionary compressive sensing [7, 11], which is a low computational and deterministic reconstruction algorithm, the proof-of-principle system experimentally achieved continuous imaging at a 1000 fps frame rate, which is approximately two orders higher than those of existing computational ghost imaging systems. The presented scheme enables us to capture images of dynamic scenes, which would be otherwise motion-blurred by other existing computational ghost imaging schemes as well as many conventional cameras
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