Survey on Feature Extraction using Neural Networks to Classify Remote Sensing Images

Remote Sensing (RS) image classification is one of the key research areas in the image processing field. The main important part of this classification is the efficient extraction of features from the RS image. The feature extraction process is also a complex process. In earlier days, there are some kind of features extracted like spectral features. But, while considering the spatial domain of the RS image, it contains more information than the spectral features. So, spectral features dominated the classification area for few years. Many researches were conducted to still improve the classification accuracy. Thus, it resulted in the extraction of features using the different neural networks, which proved to increase the accuracy. This paper surveys and discuss the different works at different duration carried out by researchers to extract the features using neural networks. Also, this survey provides a marginal overview for the future research and improvements. Citation: T. Gladima Nisia, Dr. S. Rajesh. "Survey on Feature Extraction using Neural Networks to Classify Remote Sensing Images." Global Research and Development Journal For Engineering 4.5 (2019): 41 - 45.