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Image Compression Using Stitching with Harris Corner Detector and SPIHT Coding

机译:利用Harris角检测器和SPIHT编码进行拼接的图像压缩

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摘要

An image compression technique that uses the Harris corner detector and SPIHT coding to encode images from two cameras with overlapping field of view is proposed in this paper. Firstly, the Harris corner detector is used to extract the feature points in the two images separately. Secondly, the feature points are matched and the homography that relates the two images is estimated using RANSAC. Finally, the two images are stitched together and the SPIHT coding is used to compress the stitched image. Since the resolution of the stitched image is not always fixed and difficult to be predetermined, the tree structure that is adopted by the SPIHT coding is slightly modified to resolve the problem. Generally, this technique can also be viewed as an alternative solution for joint sources image compression. The simulation results show that the file size can be reduced by approximately 14.25-25.49% depending on the amount of the overlapping region.
机译:本文提出了一种图像压缩技术,该技术使用哈里斯角检测器和SPIHT编码来编码来自具有重叠视场的两个摄像机的图像。首先,使用哈里斯角点检测器分别提取两个图像中的特征点。其次,匹配特征点,并使用RANSAC估计与两个图像相关的单应性。最后,将两个图像缝合在一起,并使用SPIHT编码压缩缝合的图像。由于缝合图像的分辨率并不总是固定的并且难以预定,因此略微修改了由SPIHT编码采用的树结构以解决该问题。通常,此技术也可以视为联合源图像压缩的替代解决方案。仿真结果表明,根据重叠区域的数量,文件大小可以减少大约14.25-25.49%。

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