Image super-resolution reconstruction method and system

Abstract

The present invention discloses an image super-resolution reconstruction method and a system. According to the method, firstly, the pixel data of a plurality of low-resolution images having the complementary information are acquired. Secondly, according to the pixel data, data consistency items selectively integrating brightness constancy constraints with gradient constraints are constructed and matched feature points are subjected to the initial flow vector updating treatment. Initial flow vectors are substituted into a motion estimation variation model constructed based on data consistency, and then the optimal motion flow vector of each pixel is obtained. Simultaneously, an optimal fuzzy core is constructed based on the brightness of the L0 norm and the fuzzy estimation energy function of a gradient-combined constraint image prior model. Finally, according to the optimal motion flow vector and the optimal fuzzy core, a reconstructed high-resolution image of a variational model is established. Based on the method or the system, the accuracy of motion displacement vectors and the accuracy of fuzzy parameters during the super-resolution reconstruction process can be effectively improved. As a result, an optimal super-resolution reconstruction result is obtained.

Description

technical field [0001] The invention relates to the technical field of image processing and quality improvement, in particular to an image super-resolution reconstruction method and system. Background technique [0002] Due to the limitation of the sensor array arrangement density of the imaging system, the spectral aliasing effect caused by undersampling, the influence of the atmosphere, and the relative motion between the platform and the scene, etc., the ability to improve the spatial resolution of the image is restricted. Therefore, it is of great significance to study a processing technology to improve the spatial resolution of the image, and to improve the imaging quality and spatial resolution of the image without changing the hardware of the observation system. As an effective method to improve the spatial resolution of images, image super-resolution reconstruction technology can reconstruct one or more high-resolution images by processing one or multiple low-resolut...

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Problems solved by technology

[0003] The existing multi-image super-resolution reconstruction model is very mature and has universal applicability to most problems. In the case of super mode, the existing regularization model can solve various problems well; under ideal conditions Under the circumstances, the improvement of the model in the maximum a posteriori estimation (MAP) framework is difficult to have a great impact on the reconstruction effect, so the present invention attempts to improve the reconstruction effect by improving the accuracy of the model-related parameters

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