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Distortion correction method for large-field-of-view display device

A technology for distortion correction and display equipment, which is applied in neural learning methods, image data processing, instruments, etc., and can solve problems such as low efficiency and poor accuracy in image distortion processing.

Active Publication Date: 2016-03-23
LUOYANG INST OF ELECTRO OPTICAL EQUIP OF AVIC
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Problems solved by technology

[0003] The purpose of the present invention is to provide a distortion correction method for a large field of view display device to solve the problems of low image distortion processing efficiency and poor precision caused by the use of traditional artificial neural networks for image distortion correction

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  • Distortion correction method for large-field-of-view display device

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Embodiment Construction

[0034] The specific embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0035] The present invention establishes an artificial neural network with a double-layer hidden structure, and uses the particle swarm algorithm to solve the weights and thresholds of each layer of the artificial neural network with a double-layer hidden structure, and obtains the value corresponding to the global extremum as the value of the neural network. The weights and thresholds are substituted into the established artificial neural network for training and learning to form an image distortion correction model. Finally, the distorted image data is input into the distortion correction model for correction, and the result is the corrected image. The implementation process of this method is as follows figure 2 As shown, the specific implementation steps are as follows:

[0036] 1. Through the analysis of the digital image source by the...

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Abstract

The invention relates to a distortion correction method for a large-field-of-view display device, and belongs to the technical field of intelligent information image processing. The method comprises: establishing an artificial neural network with a dual-layer implicit structure and solving a weight and a threshold of each layer of the artificial neural network with the dual-layer implicit structure by utilizing a particle swarm algorithm; taking a value corresponding to a global extreme value as the weight and the threshold of the neural network and substituting the value into the established artificial neural network to perform training study to form an image distortion correction model; and finally inputting distortion image data into the distortion correction model to perform correction to obtain a corrected image. According to the method, the weight and the threshold of the artificial neural network are trained by adopting the particle swarm algorithm to overcome the shortcomings of local minimum, low convergence speed and the like of a conventional artificial neural network; and the method is easy to implement, good in data processing capability, high in correction precision and suitable for distortion correction of the large-field-of-view display device.

Description

technical field [0001] The invention relates to a distortion correction method for a display device with a large field of view, and belongs to the technical field of intelligent information image processing. Background technique [0002] The nonlinear dynamic mechanism of the outstanding phenomenon shows that there is a complex nonlinear mapping relationship between distorted image data and ideal image data that is difficult to describe with explicit functions. To deal with such a complex nonlinear problem, traditional mathematical statistics and fuzzy mathematics methods are There are limitations, but the artificial neural network based on nonlinear parallel computing has high modeling ability and good fitting ability when dealing with such complex nonlinear problems. However, the traditional artificial neural network has shortcomings such as slow convergence speed of local minima, which leads to low efficiency and poor accuracy of image distortion processing. Contents of...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T3/00G06N3/08
CPCG06N3/088G06T3/04
Inventor 田立坤
Owner LUOYANG INST OF ELECTRO OPTICAL EQUIP OF AVIC
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