To reduce noise in a thin, lensless camera, researchers at Tsinghua University and MIT built an imaging system with a Fresnel zone aperture (FZA). In addition to introducing a Fresnel optical element into the camera, the researchers used a compressive sensing algorithm to improve the quality of reconstructed images. The FZA was placed 3 mm in front of a CMOS image sensor. The signal recorded by the CMOS sensor was reconstructed by the compressive sensing algorithm with total variation denoising to generate an improved image of the object. Although the Fresnel zone plate could be used as an imaging element similar to the lens, its long focal length could not support a thin structure. “If we can obtain the light field on the exit plane of [the] lens, the light field on the focal plane could be reconstructed by numerical propagation,” researcher Jiachen Wu said. “Then the length of [the] imaging system can be significantly shortened.” It was a challenge to obtain the light field because the sensor could only record the intensity and not the phase information. Since holography can record an interference pattern to reproduce a light field, the researchers decided to extend the concept of holography for incoherent illumination to their lensless camera. At MIT and Tsinghua University, researchers have developed a new lensless camera using a Fresnel zone aperture. Courtesy of J. Wu, H. Zhang, W. Zhang, G. Jin, L. Cao, and G. Barbastathis. Using the FZA imaging system/CMOS sensor setup, the researchers took a series of pictures that were displayed on an LCD monitor. The incident light rays from a point on the object passed through the FZA and cast the shadow of the FZA onto the sensor. The resulting image from the camera sensor showed a distinct fringe characteristic similar to that found in a hologram. When they found that the shadow of the Fresnel zone plate had the same form as a point source hologram, the researchers surmised that the object could be encoded into a hologram by using a Fresnel zone plate under the incoherent illumination. The image could then be reconstructed by backpropagation. The quality of reconstructed images is improved greatly by the use of a compressive sensing algorithm. Courtesy of J. Wu, H. Zhang, W. Zhang, G. Jin, L. Cao, and G. Barbastathis. To reconstruct an image from a single-shot “hologram” and prevent a twin-image effect, the researchers introduced total variation constraint into the image reconstruction. In this way, the twin image, which did not meet the constraints of total variation, was eliminated. Thanks to the compressive sensing algorithm, single-shot imaging could be achieved without any calibration. The iteration process of the compressive sensing algorithm. Courtesy of J. Wu, H. Zhang, W. Zhang, G. Jin, L. Cao, and G. Barbastathis. This computational imaging architecture could improve the quality and lower the cost of lensless cameras. The FZA pattern could be placed on the glass covering the sensor, integrating the camera and sensor and simplifying fabrication. This thin, lensless camera could be used in ultrathin smartphones, home-security cameras, and autonomous vehicles. “We try to open a door for high-quality lensless cameras free of noise,” professor George Barbastathis said. “The presented technique provides a prototype for the integration of cameras and smart devices. Through a partnership between academia and industry, this technique could become practical.” The research was published in Light: Science & Applications (www.doi.org/10.1038/s41377-020-0289-9).