Image super-resolution method and image super-resolution equipment

Abstract

The invention discloses a super-resolution image generation method. The super-resolution image generation method includes inputting a real image sample into a generation network so as to output a super-resolution image sample after the generation network and a distinguishing network are preset, acquiring distinguishing probabilities outputted by the distinguishing network after the real image sample and the super-resolution image sample are outputted, determining generation network loss functions and distinguishing network loss functions according to the real image sample, the super-resolution image sample and the distinguishing probabilities, and adjusting configuration parameters of the generation network and the distinguishing network according to the generation network loss functions and the distinguishing network loss functions; receiving a low-resolution image to be processed after adjustment is completed, generating a super-resolution image of the low-resolution image according to the generation network, and subjecting the super-resolution image to visualized processing. By the super-resolution image generation method, image super-resolution effect and realness of the super-resolution image are both improved remarkably.

Description

technical field [0001] The invention relates to the field of communication technology, in particular to an image super-resolution method. The invention also relates to an image super-resolution device. Background technique [0002] Image super-resolution reconstruction technology uses a set of low-quality, low-resolution images (or motion sequences) to generate a single high-quality, high-resolution image. The application field of image super-resolution reconstruction is extremely broad, and it has important application prospects in military, medical, public security, computer vision, etc. In the field of computer vision, image super-resolution reconstruction technology may enable the transformation of images from the detection level to the recognition level, or further to the fine resolution level. [0003] Based on the image super-resolution reconstruction technology that can improve image recognition ability and recognition accuracy, the prior art proposes a single-fram...

AI Technical Summary

Problems solved by technology

[0007] The invention provides a super-resolution image generation method to better retain the detailed information of the image to be processed, and solve the problem in the prior art that the texture details of the output high-resolution image are not clear when the sampling factor is large

Images