A Review of Image Compressed Sensing in Deep Learning

Abstract

In recent years, deep learning has developed rapidly in the field of image recognition, which provides a new idea for the reconstruction of compressed sensing. The new method based on deep learning can measures the correlation between the measurement signal and the original signal through network , which not only has high reconstruction accuracy, but also significantly reduces the time consuming, showing the great potential of deep learning in the field of compressed sensing reconstruction. This paper sorts out the current image compressed sensing reconstruction methods based on deep learning, analyzes the characteristics and key steps of the algorithm according to three different deep network structures, and finally looks forward to the development direction of compressed sensing reconstruction based on deep learning.