Edge enhancement and preservation of edges to emphasize the features for images is an essential task in computer vision. The conventional operators may cause false edge detection. In this paper, a fuzzy inference system (FIS) is proposed, which combines with Wavelet (WT) based multidirectional and multilevel edge finding technique for getting good edge localization. After applying of WT decomposition on the original image, the coefficients are filtered out from horizontal, vertical, and diagonal directions. A non-linear energy operator is applied to all WT decomposition to corroborate the edge pixels. This energy calculated edge coefficients are given into the FIS for better enhancement. Since WTs allow for separation of the image into frequency bands without affecting spatial locality, the real edge pixels are further emphasized.
Optimizing 4D Lookup Table for Low-light Video Enhancement via Wavelet Priori
College of Computer Science and Engineering, Chongqing University of Technology（重庆理工大学计算机科学与工程学院）；Chinese University of Hong Kong（香港中文大学）；College of Computer Science, Chongqing University（重庆大学计算机学院）
Wavelet-based Mamba with Fourier Adjustment for Low-light Image Enhancement
School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology（上海理工大学光电信息与计算机工程学院）；School of computer science and artificial intelligence, Liaoning Normal University（辽宁师范大学计算机与人工智能学院）；College of computer science and technology, Jilin University（吉林大学计算机科学与技术学院）；School of Computer, National University of Dense Technology（国防科技大学计算机学院）
Wavelet-based Decoupling Framework for low-light Stereo Image Enhancement
Shaanxi Key Laboratory for Network Computing and Security Technology（陕西网络计算与安全技术重点实验室）；School of Computer Science and Engineering（计算机科学与工程学院）；Xi'an University of Technology（西安理工大学）
Tunable Wavelet Unit based Convolutional Neural Network in Optical Coherence Tomography Analysis Enhancement for Classifying Type of Epiretinal Membrane Surgery
University of California San Diego（加州大学圣迭戈分校）；Jacobs Retina Center（雅各布视网膜中心）
Robust Real-Time Endoscopic Stereo Matching under Fuzzy Tissue Boundaries
The School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China（生物医学工程学院，上海交通大学）；Innovation Center for Electronic Design Automation Technology, Hangzhou Dianzi University, Hangzhou 310018, China（电子设计自动化技术创新中心，杭州电子科技大学）
Multi-stage image denoising with the wavelet transform
Northwestern Polytechnical University（西北工业大学）；Harbin Institute of Technology（哈尔滨工业大学）；Peng Cheng Laboratory（鹏城实验室）；University of Macau（澳门大学）；The Chinese University of Hong Kong (Shenzhen)（香港中文大学（深圳））；Shenzhen Institute of Artificial Intelligence and Robotics for Society（深圳市人工智能与机器人研究院）
LLCaps: Learning to Illuminate Low-Light Capsule Endoscopy with Curved Wavelet Attention and Reverse Diffusion
The University of Sydney（悉尼大学）；The Chinese University of Hong Kong (CUHK)（香港中文大学）；Northeastern University（东北大学）；University College London（伦敦大学学院）；Shun Hing Institute of Advanced Engineering, CUHK（香港中文大学信兴高等工程研究所）
End-to-end Triple-domain PET Enhancement: A Hybrid Denoising-and-reconstruction Framework for Reconstructing Standard-dose PET Images from Low-dose PET Sinograms
ShanghaiTech University（上海科技大学）；Shanghai United Imaging Intelligence Co., Ltd.（上海联影智能医疗科技有限公司）；Shanghai Clinical Research and Trial Center（上海临床研究与试验中心）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）
提出端到端三域 TriPLET 框架，融合投影域去噪、小波域重建和图像域对抗评估，从低剂量 PET 正弦图恢复标准剂量图像，并取得最优相似度与信噪比。
