Satellite video super-resolution reconstruction method and system based on recurrent neural network

A technology of cyclic neural network and super-resolution reconstruction, which is applied in the field of remote sensing satellite video processing, can solve the problems of satellite video image moving target deformation, not considering the shape and texture of ground objects, and poor super-resolution reconstruction effect, etc.

Active Publication Date: 2020-05-08
ZHUHAI DAHENGQIN TECH DEV CO LTD
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Problems solved by technology

The current super-resolution reconstruction is based on a single pixel, and does not consider the shape, texture and other characteristics of the ground object. Therefore, based on the current super-resolution

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  • Satellite video super-resolution reconstruction method and system based on recurrent neural network
  • Satellite video super-resolution reconstruction method and system based on recurrent neural network
  • Satellite video super-resolution reconstruction method and system based on recurrent neural network

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Embodiment Construction

[0056] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0057] see figure 1 , a method for super-resolution reconstruction of satellite video images based on a recurrent neural network provided by an embodiment of the present invention, the specific steps are as follows:

[0058] Step 1: Obtain satellite video images and extract them frame by frame to form an image sequence {I 1 ,I 2 ,...,I t ,...,I n}:

[0059] The optical satellite video image acquired in the embodiment has a spatial resolution of 0.92m, covering houses, rivers, green spaces, farmland, and moving vehicles, ships, airplanes and other static features and moving objects. Extract satellite video images frame by frame to obtain image sequences of the same area {I 1 ,I 2 ,...,I t ,...,I n}. Among them, n is the number of images, and t is the serial number of the images.

[0060] Step 2: Carry out multi-scale...

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Abstract

The invention provides a satellite video super-resolution reconstruction method and system based on a recurrent neural network. The method comprises the steps: obtaining a satellite video image, carrying out the frame-by-frame extraction, and forming an image sequence of the same region; carrying out multi-scale object segmentation on the extracted image sequence according to the shape and texturefeatures of the ground object to serve as geometric constraint conditions to ensure the integrity of the ground object, and obtaining an image sequence after multi-scale segmentation, denoted as theimage sequence as a high-resolution image sequence; simulating degradation processing in a satellite video image transmission process, and performing down-sampling, compression and noise addition on the image sequence after scale segmentation to obtain a low-resolution image sequence after degradation; constructing a deep learning network by taking the low-resolution image sequence as input and taking the current frame image as output based on a recurrent neural network; and optimizing the network, and outputting a super-resolution reconstructed video image by using the trained recurrent neural network. According to the invention, the integrity of ground objects is ensured, and the reconstruction precision of satellite video images is improved.

Description

technical field [0001] The invention belongs to the technical field of remote sensing satellite video processing, and relates to a satellite video image super-resolution reconstruction method and system based on a cyclic neural network constrained by geometric objects. Background technique [0002] In the field of remote sensing, video satellites are a new type of earth observation satellites, which are mainly realized by low-orbit video imaging satellites or agile imaging satellites. The biggest difference between the video satellite and the traditional optical remote sensing satellite is that it has a higher time resolution, can continuously observe a certain area, and obtain more information about the movement of the target in the form of video recording, which is especially suitable for moving targets. The high-resolution observation of the target can obtain the moving speed and direction of the target, and this important information is difficult to obtain by traditional...

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Application Information

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IPC IPC(8): G06T3/40G06T7/10G06N3/04
CPCG06T3/4053G06T7/10G06T2207/10016G06N3/044
Inventor 邓练兵
Owner ZHUHAI DAHENGQIN TECH DEV CO LTD
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