The super resolution reconstruction technology of remote sensing image can improve the spatial resolution of remote sensing image,enhance the detail and clarity of the image,and improve the accuracy of feature identification and information extraction in geological investigation.To reduce the loss of detail and feature information by the existing reconstruction models of remote sensing image for geology application,a multi-scale progressive enhanced deep residual super-resolution network(MPEDSR)was proposed on the enhanced deep super-resolution network.This model focuses on adjusting the residuals structure,adding skip connections to the residual stack structure,and introducing channel attention mechanism module between the residuals to make full use of the residuals branch information.The test data proves the interpretation ability of geological survey elements of the proposed method.The experimental results showed that the proposed algorithm was higher in subjective visual perception,Peak Signal-to-Noise Ratio(PSNR),Structural Similarity(SSIM)and other objective evaluation indexes than the existing algorithms.Compared with the original model,the PSNR was improved by 0.176 dB and 0.194 dB at 2x and 4x scale factors respectively.SSIM increased by 0.018 and 0.021 respectively.In addition,the network can effectively extract landslide and lithology boundaries and identify fault structures.Therefore it provides an effective technical means to improve the high-resolution remote sensing images for geological interpretation and geological hazard monitoring,and promotes the refinement and intelligent development of remote sensing geological interpretation.
super resolution reconstructionresidual networkremote sensing imagegeological interpretation
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