An offshore image super-resolution reconstruction method based on a discriminant dictionary

Abstract

The invention discloses an offshore image super-resolution reconstruction method based on a discriminant dictionary. By constructing the internal structure association between the image feature representations, THE clearer and more robust offshore image super-resolution reconstruction is realized. According to the method, a compressed sensing theory is utilized, and under a sparse coding framework, a discriminant dictionary learning solving process is constructed for solving the problem that a reconstruction result is inaccurate due to lack of structural association analysis in an image super-resolution reconstruction process. The method comprises constructing a group dictionary and a common dictionary expression according to the spatial distance of the image features; and further introducing a group sparse constraint item, a local restrictive sparse constraint item and an inconsistent penalty item, and storing inherent structure characteristics represented by image characteristics ina dictionary learning process to obtain a more accurate offshore image super-resolution reconstruction result.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method for super-resolution reconstruction of maritime images based on a discriminant dictionary. Background technique [0002] Image super-resolution reconstruction is a technology that restores low-resolution images to high-resolution images with richer information. It is widely used in various industries such as medical image analysis, face recognition, and remote sensing image processing. With the continuous advancement of the intelligent development of marine information, the demand for monitoring image data processing for the marine environment continues to increase. How to carry out effective super-resolution reconstruction of the low-resolution transmission images actually taken, so as to obtain better results of maritime image analysis and processing is becoming increasingly important. [0003] Due to the lack of structural correlation analysis in the diction...

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Problems solved by technology

[0003] Due to the lack of structural association analysis in the dictionary learning process of the existing super-resolution reconstruction method based on compressed sensing theory, there is a problem that the accuracy of the reconstruction result is not high

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