Abstract: The present invention relates to a neural network-based high-resolution image restoration method and system, including: performing feature extraction on a target frame in a network input to obtain a first feature, performing feature extraction on a first frame and an adjacent frame and an optical flow between the first frame and the adjacent frame to obtain a second feature, and concatenating the first feature and the second feature to obtain a shallow layer feature; performing feature extraction and refinement on the shallow layer feature to obtain a plurality of output first features and a plurality of output second features; performing feature decoding on the plurality of output second features, and concatenating decoded features along channel dimensionality to obtain features; and performing weight distribution on the features to obtain final features, and restoring an image. The present invention can effectively help to improve image quality.

Abstract: The present invention relates to a neural network-based high-resolution image restoration method and system, including: performing feature extraction on a target frame in a network input to obtain a first feature, performing feature extraction on a first frame and an adjacent frame and an optical flow between the first frame and the adjacent frame to obtain a second feature, and concatenating the first feature and the second feature to obtain a shallow layer feature; performing feature extraction and refinement on the shallow layer feature to obtain a plurality of output first features and a plurality of output second features; performing feature decoding on the plurality of output second features, and concatenating decoded features along channel dimensionality to obtain features; and performing weight distribution on the features to obtain final features, and restoring an image. The present invention can effectively help to improve image quality.