Compressed sensing sampling reconstruction method and system based on linear sampling network and generative adversarial residual network

• Main Authors: CHAI XIULI, LU YANG, GAN ZHIHUA, FU JIANGYU, TIAN YE, WANG YINJING
• Format: Patent
• Language: Chinese; English
• Published: 22.12.2020
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; HANDLING RECORD CARRIERS; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS

The invention discloses a compressed sensing sampling reconstruction method and system based on a linear sampling network and a generative adversarial residual network. The method comprises the steps:obtaining a training image, and segmenting the training image into a plurality of image blocks through segmentation processing; constructing a linear sampling network to measure the image blocks to obtain measurement values corresponding to the image blocks; in the generative adversarial residual network, carrying out linear mapping processing on measurement values of all image blocks through a full connection layer to obtain an initial reconstruction result; inputting the initial reconstruction result into a residual error network, and training to obtain residual error information; performing signal fusion on the initial reconstruction result and the residual error information to obtain a generation result of the generator; jointly inputting a generation result of the generator and the original image block into