基于生成网络的遥感图像超分辨率的研究
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摘要
提出了一种基于生成器网络的遥感图像超分辨率方法。该方法对网络的权重随机初始化,无需使用数据集进行预训练。输入待修复的低分辨率图像,通过迭代训练网络,生成网络输出边缘更为清晰的超分辨率图像。对遥感图像上复杂纹理的修复也达到了更清晰的预期效果。实验结果表明,生成网络能在遥感图像超分辨率上达到经过大量数据集训练的卷积神经网络相似甚至更好的表现。
A remote sensing image super-resolution method based on generator network is proposed. This method does not require data sets for pre-training,and weights in it are randomly initialized. Low resolution image is imported into the generator network,which can output sharper high resolution image through iterative training. The effect of generator network on the restoration of complex texture on remote sensing images has achieved the expected results. Experimental results show that non-preconditioned generation network can achieve the similar or even better performance of the convolutional neural network trained by a large number of data sets at super-resolution of images.
A remote sensing image super-resolution method based on generator network is proposed. This method does not require data sets for pre-training,and weights in it are randomly initialized. Low resolution image is imported into the generator network,which can output sharper high resolution image through iterative training. The effect of generator network on the restoration of complex texture on remote sensing images has achieved the expected results. Experimental results show that non-preconditioned generation network can achieve the similar or even better performance of the convolutional neural network trained by a large number of data sets at super-resolution of images.
引文
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[12] A. M,A. V. Understanding deep image representations by inverting them[C]//2015 IEEE Conference on Computer Vision and Pattern Recognition(CVPR). New York:IEEE Press,2015:5188-5196.
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[15] Kingma D P,Ba J. Adam:A method for stochastic optimization[DB/OL].(2017-1-30)[2018-9-20]. https://arxiv. org/pdf/1412. 6980. pdf.
[16] Bahdanau D,Cho K,Bengio Y. Neural machine translation by jointly learning to align and translate[DB/OL].(2016-5-19)[2018-9-20]. https://arxiv. org/pdf/1409. 0473. pdf.
[17]陆敏俊,王慈.基于相关性的JPEG高压缩图像峰值信噪比盲估计[J].计算机工程,2017,43(8):253-257.
[18]徐少平,杨荣昌,刘小平.信息量加权的梯度显著度图像质量评价[J].中国图象图形学报,2014,19(2):201-210.