Saturday, July 27, 2024

Bifocal camera developed with a depth of field of 3 cm at 1.7 km

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from Valentin Sattler
Researchers have succeeded in developing a bifocal camera that can still take sharp images even at great distances from the object. To do this, bifocal lenses are used, which project the incident light onto two focal planes.

Just like human eyes, cameras also have problems. One of these is depth of field: normally only one distance can be truly in focus at a time. Objects that are closer or further away are increasingly blurred. A bifocal camera has now been featured in the scientific journal Nature, which aims to largely circumvent this problem.

Two levels of sharpness

The researchers are said to have succeeded in developing a bifocal lens that can focus at two different distances at the same time. The model used for the construction was meanwhile extinct trilobites Dalmanitin socialiswho possessed this same ability. This allowed him to simultaneously identify nearby food and predators from a distance.

To replicate this ability, the researchers relied on numerous etched lenses. These can break up incoming light rays differently depending on their polarization. As a result, left-polarized light is reflected from a different focal plane than right-polarized light. The end result is a sharp image at a distance of 3 cm and 1.7 km at the same time.






Images taken with the camera are assembled into a consistently sharp overall image using deep learning.

Source: Nature





Also interesting: Superconducting Computing: Researchers discover a superconductor that only conducts electricity in one direction

A neural network is used to obtain a sharp image of the intervening area as well. Apparently this can also compute sharp images for intermediate distances, so that the developed camera with its bifocal lens can produce images with an enormous depth of field. It is said that there are many possible uses for this type of recording: in their work, the researchers speak, for example, of microscopy, automatic image recognition, and also of classical photography.

Source: Nature / Phys.org

Ebenezer Robbins
Ebenezer Robbins
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