Research Article
Texture Image Feature Enhancement Processing Method Based on Visual Saliency Model
@INPROCEEDINGS{10.1007/978-3-031-50546-1_31, author={Yuan Wang}, title={Texture Image Feature Enhancement Processing Method Based on Visual Saliency Model}, proceedings={Advanced Hybrid Information Processing. 7th EAI International Conference, ADHIP 2023, Harbin, China, September 22-24, 2023, Proceedings, Part II}, proceedings_a={ADHIP PART 2}, year={2024}, month={3}, keywords={Texture Images Feature Enhancement Noise Reduction Processing Visual Saliency Model Feature Extraction}, doi={10.1007/978-3-031-50546-1_31} }- Yuan Wang
Year: 2024
Texture Image Feature Enhancement Processing Method Based on Visual Saliency Model
ADHIP PART 2
Springer
DOI: 10.1007/978-3-031-50546-1_31
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.
