This paper proposes a cat-eye effect target recognition method with compressive sensing (CS) and presents a recognition method (sample processing before reconstruction based on compressed sensing, or SPCS) for image processing. In this method, the linear projections of original image sequences are applied to remove dynamic background distractions and extract cat-eye effect targets. Furthermore, the corresponding imaging mechanism for acquiring active and passive image sequences is put forward. This method uses fewer images to recognize cat-eye effect targets, reduces data storage, and translates the traditional target identification, based on original image processing, into measurement vectors processing. The experimental results show that the SPCS method is feasible and superior to the shape-frequency dual criteria method.
© 2013 Optical Society of America
Instrumentation, Measurement, and Metrology
Original Manuscript: May 14, 2013
Revised Manuscript: September 10, 2013
Manuscript Accepted: September 10, 2013
Published: September 30, 2013
Li Li, Hui Li, Ersheng Dang, and Bo Liu, "Compressive sensing method for recognizing cat-eye effect targets," Appl. Opt. 52, 7033-7039 (2013)