Image processing method and device based on deep learning and electronic device

An image processing and deep learning technology, applied in the field of image processing, can solve the problems of high cost, low quality of decoded image, distortion of decoded image, etc., to achieve the effect of high speed, low cost, and labor saving.

Active Publication Date: 2019-12-03
北京威睛光学技术有限公司
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Problems solved by technology

[0002] The traditional image processing technology uses Wiener filter decoding, the quality of the decoded image is low, and in the wavefront phase encoding process, due to the existence of processing errors, the decoded image has obvious distortion, and the cost of processing these distortions is high

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  • Image processing method and device based on deep learning and electronic device

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Embodiment Construction

[0032] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0033] It should be noted that all expressions using "first" and "second" in the embodiments of the present invention are to distinguish two entities with the same name but different parameters or parameters that are not the same, see "first" and "second" It is only for the convenience of expression, and should not be construed as a limitation on the embodiments of the present invention, which will not be described one by one in the subsequent embodiments.

[0034] A wavefront encoded camera is an encoded camera capable of achieving a large depth of field. The technology is divided into encoding technology and decoding technology in detail. The encoding process is implemented in the lens design, and the thickness of the r...

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Abstract

The invention discloses an image processing method and device based on deep learning, and an electronic device. The image processing method comprises the steps of collecting first image data; generating second image data according to the first image data; constructing a data set by using the first image data and the second image data; constructing a forward-reverse convolutional neural network model; training the forward-inverse convolutional neural network model by using the data set; and carrying out image processing by using the trained forward-inverse convolutional neural network model. According to the invention, correction of various errors occurring when a wavefront coded image is decoded by using a traditional method is realized, a clear image with defocus blur removed is finally obtained, super-large depth-of-field imaging is realized, a high-quality image is obtained, the speed is faster, the process is simpler, manpower is saved, and the image processing cost is effectivelyreduced.

Description

technical field [0001] The present invention relates to the field of image processing, in particular to an image processing method, device and electronic equipment based on deep learning. Background technique [0002] The traditional image processing technology uses Wiener filter decoding, the quality of the decoded image is low, and in the wavefront phase encoding process, due to the existence of processing errors, the decoded image has obvious distortion, and the cost of processing these distortions is high. Contents of the invention [0003] In view of this, the purpose of the present invention is to provide a high-quality, low-cost image processing method, device and electronic equipment. [0004] Based on the above-mentioned purpose, the present invention provides a kind of image processing method based on deep learning, it is characterized in that, comprises: [0005] collecting first image data; generating second image data according to the first image data; [00...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T9/00G06N3/04
CPCG06T5/002G06T9/002G06T2207/20081G06T2207/20084G06N3/045
Inventor 柳淳杨正贤孙琼阁韩鹏飞
Owner 北京威睛光学技术有限公司
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