A camera that produces 3D images from a single 2D image without any lenses has been developed. The camera, which is called DiffuserCam, is compact and reportedly inexpensive to construct because it consists of only a diffuser placed on top of an image sensor. Although the hardware is simple, the software it uses to reconstruct high-resolution 3D images is very complex.
"The DiffuserCam can, in a single shot, capture 3D information in a large volume with high resolution," said the research team leader Laura Waller, University of California, Berkeley. "We think the camera could be useful for self-driving cars, where the 3D information can offer a sense of scale, or it could be used with machine learning algorithms to perform face detection, track people, or automatically classify objects."
In a recently published paper in Optica, the researchers show that the DiffuserCam can be used to reconstruct 100 million voxels, or 3D pixels, from a 1.3-megapixel image without any scanning. For comparison, the iPhone X camera takes 12-megapixel photos.
"Our new camera is a great example of what can be accomplished with computational imaging—an approach that examines how hardware and software can be used together to design imaging systems," said Waller. "We made a concerted effort to keep the hardware extremely simple and inexpensive. Although the software is very complicated, it can also be easily replicated or distributed, allowing others to create this type of camera at home."
A DiffuserCam can be created using any type of image sensor and can image objects that range from microscopic in scale all the way up to the size of a person. It offers a resolution in the tens of microns range when imaging objects close to the sensor. Although the resolution decreases when imaging a scene farther away from the sensor, it is still high enough to distinguish that one person is standing several feet closer to the camera than another person, for example.
The new camera will be used in a project at University of California Berkeley that aims to watch a million individual neurons while stimulating 1,000 of them with single-cell accuracy. As a first step, the researchers want to create what they call a cortical modem that will "read" and "write" to the brains of animal models, much like the input-output activity of internet modems. The DiffuserCam will be the heart of the reading device for this project, which will also use special proteins that allow scientists to control neuronal activity with light.
"Using this to watch neurons fire in a mouse brain could in the future help us understand more about sensory perception and provide knowledge that could be used to cure diseases like Alzheimer's or mental disorders," Waller adds.
The open source software for the DiffuserCam is available on the project page.
Image: The lensless DiffuserCam consists of a diffuser placed in front of a sensor (bumps on the diffuser are exaggerated for illustration). The system turns a 3D scene into a 2D image on the sensor. After a one-time calibration, an algorithm is used to reconstruct 3D images computationally. The result is a 3D image reconstructed from a single 2D measurement. Image courtesy of Laura Waller, University of California, Berkeley.