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Intrinsic Image Decomposition Method Based on Unet-based Jump Layer Frequency Division and Multi-Scale Discrimination

An intrinsic image, multi-scale technology, applied in the field of image processing, can solve the problem of many high-frequency components, and achieve the effect of solving the problem of feature equivalence

Active Publication Date: 2022-03-11
NORTHWESTERN POLYTECHNICAL UNIV
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  • Summary
  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

On the other hand, adding frequency decomposition and frequency compression to the skip connection of the light map can not only get a more suitable feature map but also solve the problem of high frequency components in the light map

Method used

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  • Intrinsic Image Decomposition Method Based on Unet-based Jump Layer Frequency Division and Multi-Scale Discrimination
  • Intrinsic Image Decomposition Method Based on Unet-based Jump Layer Frequency Division and Multi-Scale Discrimination
  • Intrinsic Image Decomposition Method Based on Unet-based Jump Layer Frequency Division and Multi-Scale Discrimination

Examples

Experimental program
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Embodiment

[0126] (1) Build a training image sample library

[0127] Using the MPI image dataset, there are 9 categories of scenes commonly used in the MPI dataset, each category has two subcategories, and each category has 50 pictures. There are two segmentation methods when constructing the training image sample library, one is based on the image-split method, and the other is the scene-split method.

[0128] In the image-split method, in the 18 small categories of the image data set, half of the images are extracted for each small category, and each image size is 1024x436, and 10 small images with a size of 256x256 are randomly sampled in the image, and then the The small images are flipped horizontally so that each image gets 20 small images. The total number of training data sets is 9000 (18x25x20) small images with a size of 256x256, and the test data set uses the original image size, with a total of 450 (18x25) large images with a size of 1024x436.

[0129] In the Scene-split me...

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Abstract

The present invention provides an intrinsic image decomposition method based on Unet-based jump layer frequency division and multi-scale identification, and constructs a Unet-based generation confrontation network, which is composed of a generator and a discriminator, and the generator is used to decompose the image into Reflection map and illumination map, the role of the discriminator is to distinguish the authenticity of the image, and guide the generator to generate a fake image. The network designed by the invention effectively alleviates the problem caused by the features of the encoder being directly sent to the decoder. On the one hand, the constraint of frequency decomposition is added to the skip connection of the reflection map Unet, so that the network can learn the importance of different features and get more suitable features. On the other hand, adding frequency decomposition and frequency compression to the skip connection of the light map can not only obtain a more suitable feature map but also solve the problem of high-frequency components in the light map.

Description

technical field [0001] The invention belongs to the field of image processing, and in particular relates to an intrinsic image decomposition method. Background technique [0002] Image recognition applications have appeared in various places of life, such as face recognition, target tracking, driverless driving, etc. However, in the imaging process, due to the influence of many environmental factors such as light intensity, light incident angle, and shadow occlusion, the imaging effect may be poor, which makes image recognition difficult and the accuracy is reduced. One way to solve this problem is to extract features that do not change with environmental factors in multi-modal images, that is, intrinsic images. Intrinsic image refers to the inherent characteristics of an object independent of environmental factors, including color, texture, material, etc. These inherent characteristics will not change with changes in environmental factors. By separating the intrinsic info...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/04G06N3/08G06T5/00
CPCG06N3/08G06T2207/20081G06T2207/20084G06N3/048G06N3/045G06T5/70
Inventor 蒋晓悦方阳王鼎李煜祥冯晓毅
Owner NORTHWESTERN POLYTECHNICAL UNIV