AmericaDespite its ultra-small size, the new camera model can capture color images with the same quality as conventional lenses 500,000 times larger.
The new ultra-compact optical device was developed by a team from Princeton University and the University of Washington. The device overcomes the problem of previous micro-camera designs, which often produced distorted and blurry images with a very limited field of view. The new camera could allow the micro-robot to detect its surroundings, even helping doctors search for problems within the human body.
Conventional large cameras use a series of glass or plastic lenses that deflect the beam of light striking the focal point of the film or digital sensor. In contrast, the small camera developed by computer scientist Ethan Tseng and his colleagues is based on a special ultra-thin surface with 1.6 million pillars, each the size of an HIV virus, that can adjust the orientation of light. .
Each 0.5mm wide surface column is uniquely shaped allowing it to function as an antenna. The machine learning algorithm then decodes the interaction of each column with the light, transforming it into an image. Images taken from this microdevice provide the highest quality images with the widest field of view of any ultrathin color camera ever developed.
Previous designs tended to suffer from distortion, limited field of view, and problems capturing the full spectrum of visible light due to their reliance on primary color combinations such as red, green, and blue to create other colors.
In addition to being slightly blurry near the edge of the frame, photos taken with the new tiny camera can be compared to a normal large camera equipped with 6 refracting lenses. The camera can also perform well in natural light rather than having to use a laser or requiring ideal conditions like previous ultrathin cameras to produce high-quality images.
To overcome the difficulty of having millions of tiny microstructures on an ultra-thin surface, optics expert Shane Colburn from the University of Washington creates a digital model that simulates the design of the camera with the resulting images, allowing them to evaluate and refine the setting. According to Colburn, the large number of antennas on each surface and the complexity of their interactions with light means that each simulation uses a large amount of memory and time.
The team is currently working to add more computing power to the camera, helping to improve image quality and detect objects. They published the study in a journal. Communications from nature on 11/29.
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