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Method for removing shadow of single image by edge attention based on semi-supervised learning

A semi-supervised learning and supervised learning technology, applied in the field of image lighting editing, can solve the problems of color distortion, obvious shadow boundary, and poor shadow removal effect in complex scenes, so as to enhance the detection ability, reduce the intra-class variance, enhance the The effect of performance

Pending Publication Date: 2021-11-09
WUHAN UNIV
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Problems solved by technology

[0003] The present invention provides a shadow detection and elimination network based on semi-supervised learning, aiming to solve the problem that the existing shadow elimination method has poor shadow elimination effect on real complex scenes, the shadow boundary is obvious, the processing result has color distortion, and it is difficult to meet the actual situation. Application Requirements Questions

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  • Method for removing shadow of single image by edge attention based on semi-supervised learning
  • Method for removing shadow of single image by edge attention based on semi-supervised learning
  • Method for removing shadow of single image by edge attention based on semi-supervised learning

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Embodiment 1

[0024] An embodiment of an image shadow detection and elimination method based on semi-supervised learning provided by the present invention can better realize shadow removal for shadow areas in complex scene images.

[0025] Such as figure 1 As shown in , it is a schematic diagram of the overall network of image shadow detection and elimination in this embodiment. It randomly inputs an image with a shadow, and obtains the input features of the attention network through down-sampling to the encoder, and then uses the features at different scales to generate a shadow detection map of the input image through the attention module and decoder; The shared encoder is directly decoded by the decoder in the shadow elimination network, and then performs a dot product operation with the shadow mask image output by the shadow detection network, and the final shadow elimination feature is obtained through a deep feature fusion elimination network, and finally compared with the original i...

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Abstract

The invention relates to the field of shadow elimination in image processing, and provides a method for removing a shadow of a single image based on semi-supervised edge attention. The method comprises a generator and a discriminator, wherein the generator is divided into a shadow detection network, an edge attention module and a shadow elimination network. Through the training of the semi-supervised learning network, the shadow region of the shadow image of the complex scene can be detected, the shadow image is guided to perform shadow elimination, and a better shadow-eliminated image is obtained.

Description

technical field [0001] The invention relates to a single image shadow removal method based on semi-supervised learning edge attention, especially capable of removing complex shadows in real scenes. The invention belongs to the field of image illumination editing, in particular to a shadow removal method based on semi-supervised learning. Background technique [0002] At present, the commonly used shadow removal methods can be mainly divided into the following two categories: 1. Methods based on traditional physics, such as the shadow removal method proposed in the paper "Single-image shadow detection and removal using paired regions", through physical models. Analyzes the light intensity of an image group by pixel. This method can achieve a good shadow removal effect under certain assumptions, but because it is very dependent on the acquisition of prior knowledge and a series of related assumptions, the generalization ability of this method is poor, and it cannot handle sha...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06T5/50G06N3/04G06N3/08
CPCG06T5/50G06N3/08G06T2207/20221G06N3/047G06N3/048G06N3/045G06T5/77Y02T10/40
Inventor 肖春霞朱云罗飞
Owner WUHAN UNIV
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