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A satellite image super-resolution method based on adversarial network and aerial image a priori

A satellite image and aerial image technology, applied in the field of image super-resolution, can solve problems such as non-paired nature

Active Publication Date: 2018-12-18
XI AN JIAOTONG UNIV +1
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Problems solved by technology

The current aerial image data and satellite image data do not have a paired nature, that is, they are not taken at the same place and at the same time.

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  • A satellite image super-resolution method based on adversarial network and aerial image a priori
  • A satellite image super-resolution method based on adversarial network and aerial image a priori
  • A satellite image super-resolution method based on adversarial network and aerial image a priori

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Embodiment Construction

[0074] The present invention provides a satellite image super-resolution method based on multi-scale perceptual loss and generative confrontation network combined with aerial image prior. Noise model, and then use clear aerial data to train image super-resolution model. Since there is no pair of satellite images and aerial images, when post-processing the generated super-resolution images, the clear aerial images are used to construct the external prior dictionary of the GMM model, and thus guide the internal unclear satellite images to be reconstructed . After reconstruction, in order to further improve the image quality, the Gaussian filter is used for image sharpening. Finally, the high-resolution image of the original satellite image is obtained, and the visual quality of the image is improved based on the original satellite image. The effectiveness of this scheme can also be seen from the experimental link. It provides an effective idea to solve the satellite image sup...

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Abstract

The invention discloses a satellite image super-resolution method combining an adversarial network with an aerial image a priori. Firstly, an image pair composed of a 16-level noisy image and a corresponding 16-level non-noisy image is used for training a denoising model, and then the image super-resolution model is trained by using clear aerial data. Because there is no satellite image and aerialimage pairs, clear aerial images are used to construct an external priori dictionary of GMM model in the post-processing of the generated super-resolution images, and then the internal unclear satellite images are guided to be reconstructed. In order to further improve the image quality, Gaussian filter is used to sharpen the image after reconstruction. Finally, the high-resolution image of the original satellite image is obtained, and the visual quality of the image is improved based on the original satellite image. The effectiveness of the scheme can also be seen from the experiment. It provides an effective way to solve the problem of satellite image super-resolution and image quality improvement under the condition of conditional constraints in reality.

Description

technical field [0001] The invention belongs to the technical field of image super-resolution, in particular to a satellite image super-resolution method based on multi-scale perceptual loss and generation confrontation network combined with aerial image prior. Background technique [0002] Image resolution is an important indicator of image quality. An image with higher resolution can show more details more clearly. However, due to the influence of hardware and external environment during the image acquisition process, the acquired image resolution is lower, resulting in The problem of how to obtain high-resolution images from low-resolution images. At present, with the increase in the number of satellites, satellites can cover more than 90% of the earth, which makes the range that can be monitored by satellites much larger than the range covered by images obtained by other means, but satellite images are affected by many reasons. The rate is lower. For example, compared ...

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Application Information

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IPC IPC(8): G06T3/40
CPCG06T3/4053
Inventor 黄源侯兴松赵世正
Owner XI AN JIAOTONG UNIV
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