Читать книгу Change Detection and Image Time-Series Analysis 1 - Группа авторов - Страница 15

The current development of unsupervised CD techniques for multispectral remote sensing images has had great success in many practical applications. However, there are still open issues and challenges that deserve to be further analyzed, which include but are not limited to the following:

1 1) a high-precision multitemporal pre-processing procedure, for example, co-registration techniques;

2 2) multitemporal data quality improvement due to bad imaging conditions, such as system noise, cloud contamination and seasonal spectral variations;

3 3) advanced techniques for correctly estimating the real number of multiclass changes in image scenarios;

4 4) spectral–spatial modeling of change targets to enhance the original pixel-wise spectral representation;

5 5) robust and efficient CD approach in an unsupervised fashion, especially for a large complex CD scene;

6 6) change feature representation by taking advantage of both machine learning and deep learning techniques.