Assessment method for camouflage performance based on visual perception. (November 2022)

• Record Type: Journal Article
• Authors: Li, Yumei; Liao, Ningfang; Deng, Chenyang; Li, Yasheng; Fan, Qiumei
• Is Part Of: Optics and lasers in engineering. Volume 158(2022)
• Publication Date: 2022-11
• Subjects: Camouflage effectiveness -- Image color appearance -- Image processing -- Comprehensive camouflage assessment; Lasers in engineering -- Periodicals; Optical measurements -- Periodicals; Optics -- Periodicals; Lasers en ingénierie -- Périodiques; Mesures optiques -- Périodiques; Optique -- Périodiques; 621.36605
• DOI: 10.1016/j.optlaseng.2022.107152
• Languages: English
• ISSNs: 0143-8166

Abstract

Highlights: The proposed model is comprehensive, including image color, structure, and texture. The iCAM is applied in camouflage effect assessment for the first time. The weights of the model are determined by subjective evaluation results. The proposed model improves the consistency with human visual perception. Abstract: Camouflage stealth is of great significance in concealing military targets and countering military reconnaissance, but the assessment methods for camouflage performance remain some problems, such as incomplete evaluation indexes and inconsistency with the visual perception. This study proposes a comprehensive assessment model, named comprehensive similarity, C S s u b for short. The model bases on subjective visual evaluation and contains three metrics of image color appearance, structure, and texture. The metrics are analysed by the image color appearance similarity (ICAS), structure similarity (ISS), and texture similarity (ITS), respectively, to measure the camouflage effectiveness between background and camouflage target images. The three weights, in C S s u b, are fitted through the results of subjective experiments. In the experiments, five ships are camouflaged in six sea states, a total of 30 camouflage scenes. Finally, seven evaluation methods, including the proposed model, are analyzed, and compared to predict camouflage effectiveness. The results show that C S s u b model has the best prediction performance. And the ICAS index, which is applied in camouflage assessment for the first time, accounts for a significant weight in the model, indicating that color has a great impact on image perception. So, this method based on visual perception has more superiority than others and can be used as an accurate and reliable assessment model in predicting camouflage performance.