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Training Method and Device for an Image Enhancement Model, and Storage Medium

机译:用于图像增强模型的训练方法和设备,以及存储介质

摘要

Aspects of the disclosure provide a training method and device for an image enhancement model and a storage medium. The method can include inputting each training input image group into the image enhancement model to obtain a predicted image output by the image enhancement model, and training the image enhancement model until convergence through each loss function respectively corresponding to each training pair. Each loss function can include a plurality of gray scale loss components corresponding to a plurality of frequency intervals one to one, and each gray scale loss component is determined based on a difference between a gray scale frequency division image of each predicted image and a gray scale frequency division image of the corresponding target image in each frequency interval, and different gray scale loss components correspond to different frequency intervals.
机译:本公开的各方面提供了一种用于图像增强模型和存储介质的训练方法和设备。 该方法可以包括将每个训练输入图像组输入到图像增强模型中,以通过图像增强模型获取预测的图像输出,并训练图像增强模型,直到通过分别对应于每个训练对对应的每个损耗功能来训练图像增强模型。 每个损耗函数可以包括与多个频率间隔对应的多个灰度丢失分量,并且基于每个预测图像的灰度频率划分图像和灰度级之间的差异来确定每个灰度抑制分量 每个频率间隔中的相应目标图像的频分图像,不同的灰度损耗分量对应于不同的频率间隔。

著录项

  • 公开/公告号US2021390340A1

    专利类型

  • 公开/公告日2021-12-16

    原文格式PDF

  • 申请/专利权人 BEIJING XIAOMI PINECONE ELECTRONICS CO. LTD.;

    申请/专利号US202117147714

  • 发明设计人 LIANG ZHANG;

    申请日2021-01-13

  • 分类号G06K9/62;G06T5;G06T5/50;G06T7/13;G06T7/174;G06T7/90;

  • 国家 US

  • 入库时间 2022-08-24 22:51:31

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