Image processing method and image processing system

Abstract

The invention provides an image processing method and an image processing system. The image processing method comprises the following steps: receiving an original image, and reducing the size of the original image to obtain a first transition image; providing a first expansion convolutional neural network, and performing expansion convolution processing on the first transition image by using the first expansion convolutional neural network to enhance the image quality of the first transition image so as to obtain a second transition image; amplifying the size of the second transition image toobtain a third transition image, the size of the third transition image being the same as the size of the original image; splicing the original image with the third transition image matrix to obtain afourth transition image; and providing a second expansion convolutional neural network, and performing expansion convolution processing on the fourth transition image by using the second expansion convolutional neural network to recover detail information of the fourth transition image so as to obtain a target image. According to the invention, under the condition that detail information of the image is not reduced, the calculation amount of the neural network is reduced, and local mutation of the processed image is avoided.

Description

technical field [0001] The invention relates to the field of display technology, in particular to an image processing method and an image processing system. Background technique [0002] With the development of science and technology, people have higher and higher requirements for display devices, and lighter, clearer and more colorful TVs have become the development direction and goal of TVs. In addition to improving the TV resolution on the hardware, increasing the dynamic range and color gamut range, etc., the image signal can be optimized one by one through the image processing system set in the display device to direct and coordinate the functions of the display device, so that it can be used in the existing On the basis of hardware, it brings better picture quality to users, [0003] Image enhancement technology is a kind of image processing technology, which can significantly improve image quality, make image content more layered and subjective observation effect mor...

AI Technical Summary

Problems solved by technology

[0006] Due to the characteristics of the expanded convolution, the expanded convolutional neural network can maintain a small number of calculations while expanding the field of view of the neural network, and realize the output of the neural network with the pixel accuracy of the original image. However, for large-scale images, the expanded convolutional neural network There is a problem of local mutation of the image due to insufficient field of view. For this problem, the existing technology is forced to deepen the network depth, resulting in redundant network capacity and increased complexity of the network architecture.

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