Pixel partition method using Markov random field for measurements of closely spaced objects by optical sensors

Xueying Wang; Jun Li; Weidong Sheng; Wei An; Qinfeng Du

doi:10.1117/12.2194348

12 October 2015 Pixel partition method using Markov random field for measurements of closely spaced objects by optical sensors

Xueying Wang, Jun Li, Weidong Sheng, Wei An, Qinfeng Du

Author Affiliations +

Proceedings Volume 9639, Sensors, Systems, and Next-Generation Satellites XIX; 963925 (2015) https://doi.org/10.1117/12.2194348
Event: SPIE Remote Sensing, 2015, Toulouse, France

Abstract

ABSTRACT In Space-based optical system, during the tracking for closely spaced objects (CSOs), the traditional method with a constant false alarm rate(CFAR) detecting brings either more clutter measurements or the loss of target information. CSOs can be tracked as Extended targets because their features on optical sensor’s pixel-plane. A pixel partition method under the framework of Markov random field(MRF) is proposed, simulation results indicate: the method proposed provides higher pixel partition performance than traditional method, especially when the signal-noise-rate is poor.

Citation Download Citation

Xueying Wang, Jun Li, Weidong Sheng, Wei An, and Qinfeng Du "Pixel partition method using Markov random field for measurements of closely spaced objects by optical sensors", Proc. SPIE 9639, Sensors, Systems, and Next-Generation Satellites XIX, 963925 (12 October 2015); https://doi.org/10.1117/12.2194348

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