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Content complexity adaptive video satellite compressed image super resolution method

A technology of compressing images and super-resolution, which is applied in the field of image processing, can solve problems such as inability to adapt to the variability of image content and low efficiency of super-resolution reconstruction, and achieve the effects of improving expression accuracy, reducing computation, and improving coding efficiency

Active Publication Date: 2017-07-18
ZHUHAI DAHENGQIN TECH DEV CO LTD
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Problems solved by technology

Since the training samples cannot adapt to the variability of image content, the reconstruction performance depends heavily on the completeness and volume of the training samples, resulting in extremely low super-resolution reconstruction efficiency.

Method used

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  • Content complexity adaptive video satellite compressed image super resolution method

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Embodiment Construction

[0021] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0022] In view of the fact that a video satellite image covers various types of ground objects with different textures and structures, and the regional distribution of image content complexity is inconsistent, the present invention provides a video satellite compressed image super-resolution method adaptive to content complexity, through training Multiple deep learning network models with varying content complexity select the most suitable network model for image local area blocks for reconstruction.

[0023] For the sake of simplicity, here we only distingui...

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Abstract

The invention discloses a content complexity adaptive video satellite compressed image super resolution method comprising the following steps: dividing an observation image into zones of unequal content complexity from the texture thickness and structure simple and complication angles; gathering image samples with the consistent characteristics so as to form training image sets; forming image sets of different attributes, and using each image set to train a depth learning network model; using the model matching with image different zone statistics characteristics to carry out super resolution reconstructions of the corresponding zones. The method considers content complexity differences of satellite image different natural object types, thus effectively improving the video satellite image super resolution reconstruction precision.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to an image super-resolution method, in particular to a video satellite compressed image super-resolution method. [0002] technical background [0003] Video satellite is a new type of earth observation satellite developed in recent years. Compared with traditional earth observation satellites, its biggest feature is that it can "stare" at a certain area and observe it in the form of "video recording". Obtain more dynamic information than traditional satellites, especially suitable for observing dynamic targets. Video satellites have greatly improved the dynamic observation capabilities of satellite remote sensing systems, and video satellite dynamic images are becoming an important space big data resource, widely used in resource census, disaster monitoring, ocean surveillance, continuous tracking of dynamic targets, dynamic event observation, etc. aspect. [0004] Video s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T3/40
CPCG06T3/4053
Inventor 王中元韩镇杜博邵振峰
Owner ZHUHAI DAHENGQIN TECH DEV CO LTD
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