H
Haiyang Huang
Researcher at Beijing Normal University
Publications - 23
Citations - 400
Haiyang Huang is an academic researcher from Beijing Normal University. The author has contributed to research in topics: Image segmentation & Segmentation. The author has an hindex of 9, co-authored 23 publications receiving 288 citations. Previous affiliations of Haiyang Huang include Chinese Ministry of Education.
Papers
More filters
Journal ArticleDOI
A Weighted Dictionary Learning Model for Denoising Images Corrupted by Mixed Noise
TL;DR: Rather than optimizing the likelihood functional derived from a mixture distribution, this paper presents a new weighting data fidelity function, which has the same minimizer as the original likelihood functional but is much easier to optimize.
Journal ArticleDOI
A fast segmentation method based on constraint optimization and its applications: Intensity inhomogeneity and texture segmentation
TL;DR: Compared with other approaches such as level set method, the experimental results have shown that the approach greatly improves the calculation efficiency without losing segmentation accuracy.
Journal ArticleDOI
Learning a Discriminative Distance Metric With Label Consistency for Scene Classification
Yuebin Wang,Liqiang Zhang,Hao Deng,Jiwen Lu,Haiyang Huang,Liang Zhang,Jun Liu,Hong Tang,Xiaoyue Xing +8 more
TL;DR: The proposed discriminative distance metric learning method with LC (DDML-LC) starts from the dense scale invariant feature transformation features extracted from HSR-RSIs, and then uses spatial pyramid maximum pooling with sparse coding to encode the features.
Journal ArticleDOI
Nonnegative and Nonlocal Sparse Tensor Factorization-Based Hyperspectral Image Super-Resolution
TL;DR: This article proposes a novel nonnegative and nonlocal 4-D tensor dictionary learning-based HSI super-resolution model using group-block sparsity that outperforms many state-of-the-art HSIsuper-resolution methods.
Journal ArticleDOI
Convexity Shape Prior for Level Set-Based Image Segmentation Method
TL;DR: Zhang et al. as discussed by the authors proposed an image segmentation model that incorporates convexity shape priori using level set representations, which can easily segment convex objects from images with complicated background.