All current cameras and imaging systems have the same classical problem in practical applications. To complete the observation task, a large amount of data is captured, processed, and transmitted; then most of the data is discarded because it is not essential for the given observation task. The problem comes from the principle of the cameras and imaging systems — they are all based on the traditional concept that each pixel of the image is equal in importance, and all the pixels are captured to complete the observation task. But in the most practical applications, the pixels at different parts of images usually have different importance to the observers. For given observation and recognition tasks, only a part of the pixels on one image is essential.

This innovation is a 3D imaging technology that minimizes the data redundancy in the imaging systems. The method is based on the principle of human observation and recognition. Instead of equally capturing each pixel of an image, human observation first captures the overall profile of the object, and then focuses on the interested localized areas. In this way, the most essential information needed for observation and recognition purposes can be obtained with the minimum data acquisition in the shortest time. The new method realizes the same mechanism with a simple and low-cost system. This technology can be integrated into most current 3D imaging systems with no significant hardware change. The performance of these systems can be improved significantly by having more flexibility and less data flow to complete the imaging tasks.

The core technology is a method that can give the 2D or 3D profile of the object very rapidly, and then the details are given out on the localized areas of observers most interests. By doing so, the observation task can be completed with the minimum amount of data capturing, processing, and transmission.

The system has only one photodetector, a one-pixel camera, but is capable of 3D imaging. It can realize real-time planetary exploration while producing the minimum dataflow.

This work was done by Stanley Woodard of Langley Research Center and Chuatong Wang of the National Institute of Aerospace. For more information on this technology, contact Langley Research Center at This email address is being protected from spambots. You need JavaScript enabled to view it.. LAR-18069-1

Photonics & Imaging Technology Magazine

This article first appeared in the March, 2016 issue of Photonics & Imaging Technology Magazine.

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