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A Method for Integrating Sports Information Resources Based on Fuzzy Clustering Algorithm Read chapter Read first chapter

2024 | OriginalPaper | Chapter

Texture Image Feature Enhancement Processing Method Based on Visual Saliency Model

Author : Yuan Wang

Published in: Advanced Hybrid Information Processing

Publisher: Springer Nature Switzerland

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Abstract

To improve the feature visualization effect of texture images, a texture image feature enhancement processing method based on visual saliency model is proposed. After collecting texture images, use soft and hard threshold denoising algorithms to denoise the texture images. Extract and decompose the features of the denoised image based on the visual saliency model. Based on the results of feature decomposition, the resolution of the texture image is reconstructed using deep learning technology, and then the texture image is described using shear wave transformation method to enhance the expression of the image’s feature information. According to the experiment, it can be seen that after applying this method, the distortion coefficient of the texture image is smaller and the clarity is higher, indicating the feasibility of this method.

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previous chapter Classification of Hyperspectral Remote Sensing Images Based on Three-Dimensional Convolutional Neural Network Model
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Metadata
Title
Texture Image Feature Enhancement Processing Method Based on Visual Saliency Model
Author
Yuan Wang
Copyright Year
2024
Book
Advanced Hybrid Information Processing

Print ISBN: 978-3-031-50545-4

Electronic ISBN: 978-3-031-50546-1

Copyright Year: 2024

DOI
https://doi.org/10.1007/978-3-031-50546-1_31

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