An Improved Remote Sensing Image Classification Algorithm Using a Hybrid Approach

Remote sensing image classification is a problem of great interest to researchers in the field of remote sensing. There are two main approaches to this problem: pixel-based and object-based approaches. Remote sensing images may contain multiple spectral bands and very high spatial resolution. The pixel-based approach often achieves high accuracy but encounters difficulties when classifying large-scale images such as remote sensing data. Meanwhile, the object-based approach overcomes the problem of large image size but usually provides lower accuracy compared with the pixel-based approach. This paper proposes a hybrid approach that combines both methods to develop a more effective remote sensing image classification algorithm. The proposed algorithm is evaluated on remote sensing images acquired over Hoa Binh province.