The invention relates to a compression perception reconstruction method and system based on a depth residual error network; the method comprises the following steps: obtaining original image signals as training data, and using scale transformation and segmentation treatment so as to segment the training data into a plurality of image blocks; obtaining a measuring value corresponding to the brightness component according to the brightness component of each image block and a compression perception theory model; using a fully connected network to make linear mapping treatment for the measuring value, thus obtaining a primary reconstruction result; inputting the primary reconstruction result into the depth residual error network, and training to obtain an estimated residual error value; fusingthe estimated residual error value with the primary reconstruction result so as to form reconstruction signals. The method introduces the depth residual error network so as to participate the signalreconstructions, thus restoring and reconstructing from the measuring value to the image, and using the difference between the learning and the target of the depth residual error network to improve the quality of the restored signals.
Compression perception reconstruction method and system based on depth residual error network