Patent ID: 11948278
Assignee: NATIONAL CHENGCHI UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. An image quality improvement method, comprising:
receiving an original image;
performing denoising filtering to the original image by a filter to obtain a preliminary processing image; and
inputting the preliminary processing image to a multi-stage convolutional network model to generate an optimization image through the multi-stage convolutional network model, wherein the multi-stage convolutional network model comprises a plurality of convolutional network sub-models, and the convolutional network sub-models respectively correspond to different network architectures,
wherein the convolutional network sub-models comprise a first-stage convolutional network sub-model, a second-stage convolutional network sub-model and a third-stage convolutional network sub-model, the preliminary processing image is input to the multi-stage convolutional network model, and a step of generating the optimization image through the multi-stage convolutional network model comprises:
inputting the preliminary processing image to the first-stage convolutional network sub-model to generate a first network generated image by the first-stage convolutional network sub-model;
inputting the first network generated image to the second-stage convolutional network sub-model to generate a second network generated image by the second-stage convolutional network sub-model; and
inputting the second network generated image to the third-stage convolutional network sub-model to generate the optimization image by the third-stage convolutional network sub-model,
wherein the convolutional network sub-models are generated through synchronous training based on a multi-level loss function, and the multi-level loss function comprises a weighted sum of a plurality of loss functions.