@inproceedings{ca9ce2a2c58b4d43b9aefaae20bc5a82,
title = "Image Restoration Based on Wavelet Semi-soft Threshold Transform and BP Fuzzy Neural Network",
abstract = "Image restoration aimed to recover the original image to from degraded images and degenerate function. Fuzzy logic systems and neural network can complement each other quite well. In this paper, a novel Image Restoration approach is developed. Wavelet Semi-soft Threshold Transform and of our method is utilized to image restoration. Firstly, Wavelet Semi-soft Threshold Transform method is used to image denoising. Then, the image is classified into several regions using fuzzy sets, which are smoothing, texture and edge regions to obtain the input of BP Fuzzy Neural Network. Sliding window is used to extract features and input the training data. Finally, the output of BP Fuzzy Neural Network is the restored image.",
keywords = "BP Neural Network, Fuzzy, Image restoration, Sliding window, Wavelet Semi-soft Threshold Transform",
author = "Wenjing Pei and Yingmin Jia",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2020.; Chinese Intelligent Automation Conference, CIAC 2019 ; Conference date: 20-09-2019 Through 22-09-2019",
year = "2020",
doi = "10.1007/978-981-32-9050-1\_70",
language = "英语",
isbn = "9789813290495",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "620--628",
editor = "Zhidong Deng",
booktitle = "Proceedings of 2019 Chinese Intelligent Automation Conference",
address = "德国",
}