Mr. Zhongjie Deng Profile

Zhongjie Deng

at Space Engineering University (SEU)

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Proceedings Article | 5 November 2020 Paper

Data augmentation method of remote sensing image based on transfer learning and VGG model

Zhongjie Deng, Zhenghong Dong, Fan Yang, Lurui Xia

Proceedings Volume 11565, 115650V (2020) https://doi.org/10.1117/12.2579817

KEYWORDS: Remote sensing, Data modeling, Image processing, Image enhancement, Target recognition, Neural networks

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When the human visual system processes the optical image, it will use the salient features of the target and transfer learning to perform deep processing to improve the accuracy of target recognition.The vision system can quickly transfer the existing experience to interpret the target image information, so that humans can recognize the external environment. This mechanism of applying a priori knowledge for image processing of new targets is transfer learning.This image processing method can be applied to the field of high-resolution remote sensing image processing.This paper proposes to use the transfer learning of remote sensing images and utilize the VGG model to expand the data to improve the accuracy of remote sensing image recognition tasks.In terms of innovative methods, it is proposed to use the training samples processed by the style transfer algorithm as the input of the convolutional neural network classification model, which can guide the model to learn more prior knowledge information than the data.In the algorithm design, the network parameters such as the training input, network structure, matrix expansion method and convolution kernel scale of the traditional VGG network were adjusted and optimized.The recognition accuracy experiments were conducted using CIFAR10 and DOTA datasets, and Google Earth was used.The results of random remote sensing images are verified.

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