• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of ambient intelligence and humanized computing >A study on fast SIFT image mosaic algorithm based on compressed sensing and wavelet transform
【24h】

A study on fast SIFT image mosaic algorithm based on compressed sensing and wavelet transform

机译：基于压缩感知和小波变换的快速SIFT图像拼接算法研究

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Considering the disadvantages of massive calculation and slow speed of traditional Scale Invariant Feature Transform (SIFT) algorithm, we propose an improved image mosaic method which combines Wavelet Transform (WT) and Compressed Sensing (CS) algorithm. The method works as follows. Firstly, images are transformed with wavelet and compressed using compressed sensing technology. Then, image feature points are extracted in combination with SIFT algorithm. Finally, Sequential Similarity Detection Algorithm (SSDA) with adaptive threshold is used to fast search of image matching to find out an optimal stitching line, and a panoramic image is obtained. Experimental results demonstrate that the method realizes fast image matching, efficiently overcomes the shortcomings of heavy computation and low efficiency in the process of extracting image features, and guarantees matching accuracy and stitching efficiency, which meets the real-time requestments in machine vision system. This algorithm can be applied to image matching and stitching in the field of digital image security.
机译：考虑到传统的尺度不变特征变换（SIFT）算法计算量大，运算速度慢的缺点，提出了一种结合小波变换（WT）和压缩感知（CS）算法的改进的图像拼接方法。该方法的工作原理如下。首先，利用小波变换图像，并使用压缩传感技术对其进行压缩。然后，结合SIFT算法提取图像特征点。最后，采用自适应阈值序列相似度检测算法（SSDA）对图像匹配进行快速搜索，找出最佳拼接线，得到全景图像。实验结果表明，该方法实现了图像快速匹配，有效地克服了图像特征提取过程中计算量大，效率低的缺点，保证了匹配精度和拼接效率，满足了机器视觉系统的实时性要求。该算法可以应用于数字图像安全领域中的图像匹配和拼接。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号