The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

The Remarkable Visual Abilities of Nocturnal Insects: Neural Principles and Bioinspired Night-Vision Algorithms

På svenska

Author

Summary, in English

Despite their tiny eyes and brains, nocturnal insects have remarkable visual abilities. Recent work-particularly on fast-flying moths and bees and on ball-rolling dung beetles-has shown that nocturnal insects are able to distinguish colors, to detect faint movements, to learn visual landmarks, to orient to the faint pattern of polarized light produced by the moon, and to navigate using the stars. These impressive visual abilities are the result of exquisitely adapted eyes and visual systems, the product of millions of years of evolution. Even though we are only at the threshold of understanding the neural mechanisms responsible for reliable nocturnal vision, growing evidence suggests that the neural summation of photons in space and time is critically important: even though vision in dim light becomes necessarily coarser and slower, those details that are preserved are seen clearly. These benefits of spatio-temporal summation have obvious implications for dim-light video technologies. In addition to reviewing the visual adaptations of nocturnal insects, we here describe an algorithm inspired by nocturnal visual processing strategies-from amplification of primary image signals to optimized spatio-temporal summation to reduce noise-that dramatically increases the reliability of video collected in dim light, including the preservation of color.

Publishing year

2014

Language

English

Pages

1411-1426

Publication/Series

Proceedings of the IEEE

Volume

102

Issue

10

Document type

Journal article

Publisher

IEEE Press

Topic

  • Computer Vision and Robotics (Autonomous Systems)
  • Biological Sciences
  • Mathematics

Keywords

  • Compound eye
  • denoising
  • image enhancement
  • insect
  • nocturnal vision
  • structure tensor
  • summation

Status

Published

Research group

  • Lund Vision Group

ISBN/ISSN/Other

  • ISSN: 0018-9219