红外技术2016，Vol.38Issue(8)：705-708,4.
基于纹理特征的 SIFT 算法改进
Improved SIFT Algorithm Based on Texture Features
白亚茜 1刘著平 2凌建国3
作者信息
- 1. 北京遥感设备研究所，北京 100854
- 2. 中国航天科工集团第二研究院，北京 100854
- 3. 中国航天科工集团，北京 100048
- 折叠
摘要
Abstract
An improved method used for changing the fixed threshold in Scale Invariant Feature Transform algorithm is proposed. If the texture features of the infrared image is not obvious, the feature points will be significantly reduced, so it will influence the subsequent procedure such as image registration, object recognition and etc. Modifying the contrast threshold artificially is not adapt to many occasions because of its limitation. Therefore, an adaptive contrast threshold SIFT algorithm based on texture features is necessary. Gray level co-occurrence matrix is one of the methods to represent the texture features. Owing to its feature that it could not analyze the image directly, the characteristic parameter must be extracted. The contrast threshold is modified lower only when the characteristic parameter of texture such as angular second moment becomes larger, so that the characters can be much more. The results indicate that even when the texture features of an image is not clear, large numbers of Scale Invariant Feature Transform characteristics can still be extracted.关键词
纹理特征/SIFT/自适应对比度阈值/灰度共生矩阵Key words
texture features/SIFT/adaptive contrast threshold/gray level co-occurrence matrix分类
信息技术与安全科学引用本文复制引用
白亚茜,刘著平,凌建国..基于纹理特征的 SIFT 算法改进[J].红外技术,2016,38(8):705-708,4.
