基于深度学习和双域融合的红外成像制导系统复杂背景噪声去除方法

Engineering

• Deep Learning 100%
• Guidance System 100%
• Feature Extraction 50%
• Gaussian White Noise 50%
• Signal-to-Noise Ratio 50%
• Peak Signal 50%
• Receptive Field 50%
• Convolutional Neural Network 50%
• Real Image 50%
• Comparative Experiment 50%
• Noise Suppression 50%
• Similarity Index 50%
• Gradient Information 50%
• Operating Environment 50%
• Structural Similarity 50%
• Spatial Domain 50%
• Complex Wavelet 50%
• Spatial Transforms 50%

Physics

• Signal-to-Noise Ratio 100%
• Random Noise 100%
• Convolutional Neural Network 100%
• Deep Learning 100%
• Wavelet Analysis 100%