The lucky image-motion prediction for simple scene observation based soft-sensor technology

Yan Li; Yun Su; Bin Hu

doi:10.1117/12.2191635

5 August 2015 The lucky image-motion prediction for simple scene observation based soft-sensor technology

Yan Li, Yun Su, Bin Hu

Proceedings Volume 9622, 2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology; 96220D (2015) https://doi.org/10.1117/12.2191635
Event: International Conference on Optical Instruments and Technology 2015, 2015, Beijing, China

Abstract

High resolution is important to earth remote sensors, while the vibration of the platforms of the remote sensors is a major factor restricting high resolution imaging. The image-motion prediction and real-time compensation are key technologies to solve this problem. For the reason that the traditional autocorrelation image algorithm cannot meet the demand for the simple scene image stabilization, this paper proposes to utilize soft-sensor technology in image-motion prediction, and focus on the research of algorithm optimization in imaging image-motion prediction. Simulations results indicate that the improving lucky image-motion stabilization algorithm combining the Back Propagation Network (BP NN) and support vector machine (SVM) is the most suitable for the simple scene image stabilization. The relative error of the image-motion prediction based the soft-sensor technology is below 5%, the training computing speed of the mathematical predication model is as fast as the real-time image stabilization in aerial photography.

Citation Download Citation

Yan Li, Yun Su, and Bin Hu "The lucky image-motion prediction for simple scene observation based soft-sensor technology", Proc. SPIE 9622, 2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 96220D (5 August 2015); https://doi.org/10.1117/12.2191635

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