2.3.3. Feature Embedding

The information carried by spectral images with few bands is limited. For instance, the earth's surface is seriously obscured in the water vapor bands. In the process of spectrum translation, it is difficult for the model to accurately derive the surface structure. To address this issue, feature maps are added to the input matrix to fill the lack of information in the spectrum.

Remote sensing image features include discrete features and numerical features. The semantic labels of pixels such as land surface type and cloud cover type are discrete features; the quantitative information of pixel areas such as land surface temperature and cloud cover rate are numerical features. For discrete features, this study pre-allocates a fixed number of channels for each category, and encodes the label as a one-hot vector. For numeric features, this study pre-sets the interval of the upper and lower limits of the value, and then normalizes the value to [0, 1]. Then, the size of the feature map is adjusted to that of the spectral image. Finally, the feature matrix and the spectral matrix are combined and input to the encoder.
