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Remote Sensing Image Jitter Detection and Compensation Using Convolutional Neural Network

This the code from the paper Remote Sensing Image Jitter Detection and Compensation Using Convolutional Neural Network

We use neural networks to correct the deformed remote sensing images.

Framework: python3.5 + tensorflow1.4 + keras the most latest version

Platform: Windows Spyder

Proposed architecture:

<center> <img src="https://github.com/caiya55/jitter-compensation/raw/master/fig/overview.jpg" width="70%" height="70%" /> Figure 1. Architecture of the proposed framework </center>

CNN framework

<center> <img src="https://github.com/caiya55/jitter-compensation/raw/master/fig/network.jpg" width="80%" height="80%" /> Figure 2. Architecture of the proposed neural network </center>

Experiment results on real remote sensing images are expressed below:

<center> <img src="https://github.com/caiya55/jitter-compensation/raw/master/fig/result1.jpg" width="80%" height="80%" /> Figure 3. Left: Raw deformed image; Middle: Resotred image by proposed method. Right: Resoted image by on board sensors </center> <center> <img src="https://github.com/caiya55/jitter-compensation/raw/master/fig/result2.jpg" width="80%" height="80%" /> Figure 4. Left: Raw deformed image; Middle: Resotred image by proposed method. Right: Resoted image by on board sensors </center> <center> <img src="https://github.com/caiya55/jitter-compensation/raw/master/fig/result3.jpg" width="80%" height="80%" /> Figure 4. Left: Raw deformed image; Middle: Resotred image by proposed method. Right: Resoted image by on board sensors </center>