Abstract: To detect spacecraft damage caused by hypervelocity impact, we propose an advanced spacecraft defect extraction algorithm based on infrared imaging detection. The Gaussian mixture model (GMM) is used to classify the temperature change characteristics in the sampled data of the infrared video stream and reconstruct the image to obtain the infrared reconstructed image (IRRI) reflecting the defect characteristics. The designed segmentation objective function is used to ensure the effectiveness of image segmentation results for noise removal and detail preservation, while taking into account the complexity of IRRI (that is, the required trade-offs are different). A multi-objective optimization algorithm is introduced to achieve balance between detail preservation and noise removal, and a multi-objective evolutionary algorithm based on decomposition (MOEA/D) is used for optimization to ensure damage segmentation accuracy. Experimental results verify the effectiveness of the proposed algorithm.

Key words: Hypervelocity impact damage; Defect detection; Gaussian mixture model; Image segmentation

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