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8 October 2015 Research on the optimal selection method of image complexity assessment model index parameter
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Proceedings Volume 9675, AOPC 2015: Image Processing and Analysis; 96751K (2015)
Event: Applied Optics and Photonics China (AOPC2015), 2015, Beijing, China
Target recognition is widely used in national economy, space technology and national defense and other fields. There is great difference between the difficulty of the target recognition and target extraction. The image complexity is evaluating the difficulty level of extracting the target from background. It can be used as a prior evaluation index of the target recognition algorithm's effectiveness. The paper, from the perspective of the target and background characteristics measurement, describe image complexity metrics parameters using quantitative, accurate mathematical relationship. For the collinear problems between each measurement parameters, image complexity metrics parameters are clustered with gray correlation method. It can realize the metrics parameters of extraction and selection, improve the reliability and validity of image complexity description and representation, and optimize the image the complexity assessment calculation model. Experiment results demonstrate that when gray system theory is applied to the image complexity analysis, target characteristics image complexity can be measured more accurately and effectively.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yong Zhu, Jin Duan, Xiaofei Qian, and Bo Xiao "Research on the optimal selection method of image complexity assessment model index parameter", Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 96751K (8 October 2015);

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