Image upsampling system, training method thereof and image upsampling method
First Claim
Patent Images
1. An image upsampling system, comprising:
- at least one first convolutional network and at least one muxer layer that are cascaded;
wherein an signal input end of the image upsampling system is connected with a signal input end of a first convolutional network in the at least one first convolutional network, and a signal output end of the image upsampling system is connected with a signal output end of a last muxer layer in the at least one muxer layer;
a signal input end of every muxer layer in the at least one muxer layer is connected with a signal output end of a first convolutional network located in a stage prior to the muxer layer in the at least one first convolutional network, or connected with a signal output end of another muxer layer located in a stage prior to the muxer layer in the at least one muxer layer;
the first convolutional network is configured for converting an image input to its signal input end into a plurality of feature images and outputting the feature images to the signal input end of the muxer layer connected therewith;
the muxer layer is configured for synthesizing every n×
n feature images in the feature images input to its signal input end into a feature image whose resolution is n×
n times that of the input feature image and outputting the same; and
a number of feature images input to the muxer layer is a multiple of n×
n, n being an integer greater than one.
1 Assignment
0 Petitions
Accused Products
Abstract
An image upsampling system, a training method thereof and an image upsampling method are provided, the feature images of an image are obtained by using the convolutional network, upsampling processing is performed on the images with the muxer layer to synthesize every n×n feature images in the input signal into a feature image with the resolution amplified by n×n times, in the upsampling procedure with the muxer layer, information of respective feature images in the input signal is recorded in the generated feature image(s) without loss; and thus, every time when the image passes through a muxer layer with an upsampling multiple of n, the image resolution can be increased by n×n times.
34 Citations
20 Claims
-
1. An image upsampling system, comprising:
at least one first convolutional network and at least one muxer layer that are cascaded; wherein an signal input end of the image upsampling system is connected with a signal input end of a first convolutional network in the at least one first convolutional network, and a signal output end of the image upsampling system is connected with a signal output end of a last muxer layer in the at least one muxer layer; a signal input end of every muxer layer in the at least one muxer layer is connected with a signal output end of a first convolutional network located in a stage prior to the muxer layer in the at least one first convolutional network, or connected with a signal output end of another muxer layer located in a stage prior to the muxer layer in the at least one muxer layer; the first convolutional network is configured for converting an image input to its signal input end into a plurality of feature images and outputting the feature images to the signal input end of the muxer layer connected therewith; the muxer layer is configured for synthesizing every n×
n feature images in the feature images input to its signal input end into a feature image whose resolution is n×
n times that of the input feature image and outputting the same; and
a number of feature images input to the muxer layer is a multiple of n×
n, n being an integer greater than one.- View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20)
Specification