Deep learning Based Lightweight Reconnaissance Image Compression Network
In order to meet the application requirement of low complexity image coding algorithm for small re-connaissance platforms,a lightweight reconnaissance image compression network based on deep learning was proposed.At the coding end of the lightweight reconnaissance image compression network,three convolution modules were used to map the image directly to the binary code stream conforming to uniform distribution,and the compressed data was obtained.In the convolutional module,depth-separable convolution,group convolution plus channel shuffle were adopted to reduce the number of coding end parameters and the amount of computa-tion.The decoder of lightweight reconnaissance image compression network applied to transposition convolution and residual connection to improve the ability of feature extraction and the quality of decoded image.Test results of 128×128 images showed that compared with JPGE2000,the PSNR of lightweight reconnaissance image com-pression network based on deep learning was increased by 3.85 dB,the coding time was reduced by 91%,and the lightweight coding compression of image was realized.
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