Abstract
AbstractAiming at the requirements of auto-filtering of ISAR images of space targets, a hierarchical evaluation method of ISAR image quality based on fusion features is proposed. Firstly, the overall texture, detail intensity, and signal-to-noise ratio of ISAR image are extracted, and the comprehensive features representing ISAR image quality are formed after normalization and fusion. Then, the image quality evaluation sample database is established. Combined with the manual grading evaluation results, the image quality evaluation model is trained by SVM machine learning algorithm. This method combines the advantages of subjective and objective evaluation and can realize the rapid and accurate classification of space target ISAR images.KeywordsSpace targetsISAR image quality evaluationFusion featureSVM
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