首页> 中文期刊> 《自动化学报(英文版)》 >Lightweight Image Super-Resolution via Weighted Multi-Scale Residual Network

Lightweight Image Super-Resolution via Weighted Multi-Scale Residual Network

         

摘要

The tradeoff between efficiency and model size of the convolutional neural network(CNN)is an essential issue for applications of CNN-based algorithms to diverse real-world tasks.Although deep learning-based methods have achieved significant improvements in image super-resolution(SR),current CNNbased techniques mainly contain massive parameters and a high computational complexity,limiting their practical applications.In this paper,we present a fast and lightweight framework,named weighted multi-scale residual network(WMRN),for a better tradeoff between SR performance and computational efficiency.With the modified residual structure,depthwise separable convolutions(DS Convs)are employed to improve convolutional operations’efficiency.Furthermore,several weighted multi-scale residual blocks(WMRBs)are stacked to enhance the multi-scale representation capability.In the reconstruction subnetwork,a group of Conv layers are introduced to filter feature maps to reconstruct the final high-quality image.Extensive experiments were conducted to evaluate the proposed model,and the comparative results with several state-of-the-art algorithms demonstrate the effectiveness of WMRN.

著录项

  • 来源
    《自动化学报(英文版)》 |2021年第7期|1271-1280|共10页
  • 作者单位

    Guangxi Key Laboratory of Image and Graphic intelligent processing Guilin University of Electronic Technology Guilin 541004 China;

    Guangxi Key Laboratory of Image and Graphic intelligent processing Guilin University of Electronic Technology Guilin 541004 China;

    National Local Joint Engineering Research Center of Satellite Navigation and Location Service Guilin University of Electronic Technology Guilin 541004 China;

    College of Electrical and Information Engineering Hunan University Changsha 410082 China;

    Guangxi Key Laboratory of Image and Graphic intelligent processing Guilin University of Electronic Technology Guilin 541004 China;

    National Local Joint Engineering Research Center of Satellite Navigation and Location Service Guilin University of Electronic Technology Guilin 541004 China;

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  • 正文语种 eng
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