Wu Jiachen, Zhang Hua, Zhang Wenhui, Jin Guofan, Cao Liangcai, Barbastathis George
1State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instruments, Tsinghua University, 100084 Beijing, China.
2Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 USA.
Light Sci Appl. 2020 Apr 7;9:53. doi: 10.1038/s41377-020-0289-9. eCollection 2020.
Lensless imaging eliminates the need for geometric isomorphism between a scene and an image while allowing the construction of compact, lightweight imaging systems. However, a challenging inverse problem remains due to the low reconstructed signal-to-noise ratio. Current implementations require multiple masks or multiple shots to denoise the reconstruction. We propose single-shot lensless imaging with a Fresnel zone aperture and incoherent illumination. By using the Fresnel zone aperture to encode the incoherent rays in wavefront-like form, the captured pattern has the same form as the inline hologram. Since conventional backpropagation reconstruction is troubled by the twin-image problem, we show that the compressive sensing algorithm is effective in removing this twin-image artifact due to the sparsity in natural scenes. The reconstruction with a significantly improved signal-to-noise ratio from a single-shot image promotes a camera architecture that is flat and reliable in its structure and free of the need for strict calibration.
无透镜成像消除了场景与图像之间几何同构的需求,同时允许构建紧凑、轻便的成像系统。然而,由于重建信号噪声比低,一个具有挑战性的逆问题仍然存在。当前的实现方法需要多个掩模或多次拍摄来对重建进行去噪。我们提出了一种采用菲涅耳区孔径和非相干照明的单次无透镜成像方法。通过使用菲涅耳区孔径以波前状形式对非相干光线进行编码,所捕获的图案与同轴全息图具有相同的形式。由于传统的反向传播重建受到孪生像问题的困扰,我们表明压缩感知算法由于自然场景中的稀疏性,在去除这种孪生像伪影方面是有效的。从单次拍摄图像中重建出具有显著提高的信噪比,推动了一种相机架构的发展,该架构结构扁平且可靠,无需严格校准。