Image processing method and device, equipment and storage medium

Abstract

The invention discloses an image processing method and device, equipment and a storage medium, and relates to the technical field of artificial intelligence, deep learning and image processing. The method comprises the following steps: inputting a mask image and a first image into a coding network; downsampling the first image by using each convolution layer of the coding network; enabling at least one convolution layer to determine a convolution kernel of each convolution window when a first image input into the convolution layer is subjected to convolution by inputting a mask image of the convolution layer; inputting a second image into a decoding network; and upsampling the second image by using each deconvolution layer of the decoding network, and outputting an image after the target area is filled. According to the embodiment of the invention, the convolution kernel of each convolution window during convolution of the first image in the same layer is determined through the mask image, so the method and the device can better adapt to the feature extraction of effective pixels in different convolution windows through employing the dynamic calculation convolution kernel, improvethe sensitivity of feature extraction, and finally enable the filling and restoration of an image missing area to be more reasonable.

Description

technical field [0001] This application relates to the field of computer technology, especially to the fields of artificial intelligence, deep learning, and image processing technology. Background technique [0002] When taking pictures, unwanted people or objects often appear in the image, so it is necessary to remove the unwanted content in the image and repair and reconstruct the image. When reconstructing the blank area generated by removing the unwanted content in the image, it is necessary to make a more natural filling according to the image color, texture, content and other information around the blank area in order to achieve a better image restoration. Rebuild effect. However, the current image inpainting technology has limited inpainting effects, and often cannot reasonably fill in the missing areas in the image, so it is difficult to meet the needs of users for image inpainting effects. Contents of the invention [0003] The present application provides an im...

AI Technical Summary

Problems solved by technology

However, the current image restoration technology has limited repair effects, and often cannot reasonably fill the missing areas in the image, so it is difficult to meet the needs of users for image restoration effects.

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