Application of shearlet transform in the star extraction
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摘要:为了实现高精度和高准确性的星图识别和姿态确定,本文对星点提取算法进行了研究,将剪切波变换应用到星点提取技术中。首先,通过利用剪切波变换对星图进行分解,得到不同尺度、不同方向的系数;然后,对剪切系数进行阈值处理并重构得到去噪后的星图,再对重构星图进行顶帽变换和自适应阈值处理,完成星图滤波;最后,通过质心误差补偿法提取星点的坐标,有效地完成星点提取。实验结果表明,采用剪切波变换的星图滤波对噪声去除非常有效;质心误差补偿法的误差在0.003左右,明显优于传统的质心法,基本满足星敏感器的精度高和抗干扰能力强等要求。Abstract:In order to realize high precision and high accuracy of star pattern recognition and attitude determination, the star extraction algorithm is studied and the Shearlet transform is applied to the star extraction technology. First, Shearlet transform is used for the decomposition of star image to get coefficients of different scales, different directions. Then threshold processing is used to shear coefficients and reconstruct them to get the de-noising image. Then Top-hat transform and adaptive threshold processing are used for the reconstruction image to complete the star image filtering. Finally the centroid error compensation method is used for extraction of star coordinates, which effectively completes the star extraction. The experimental results show that the noise removal is very effective with star image filtering based on shearlet transform. The error by the centroid error compensation method is about 0.003 and the method is obviously superior to the traditional centroid method. It can satisfy the star sensor requirements of high precision and strong anti-jamming.
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Key words:
- shearlet transform/
- star extracting/
- centroid compensation
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图 1剪切波变换频域剖分及支撑基的对比
Figure 1.Tiling of the frequency plane induced by Shearlet and the comparison of frequency support
图 3传统小波去噪和Shearlet去噪星图对比(σ=0.01)
Figure 3.Comparison of Star image with wavelets denoising and Shearle denoisingt(Gauss noise ofσ=0.01)
图 4传统小波去噪和Shearlet去噪星图对比(σ=0.1)
Figure 4.Comparison of Star image with wavelets denoising and Shearle denoisingt(Gauss noise ofσ=0.1)
图 5σ=0.01高斯噪声重构星图进行顶帽变换和阈值处理后星图
Figure 5.Images after Top-hat transform and threshold processing of reconstruction image with Gauss noise ofσ=0.01
图 6σ=0.1高斯噪声重构星图进行顶帽变换和阈值处理后星图
Figure 6.Images after Top-hat transform and threshold processing of reconstruction image with Gauss noise ofσ=0.1
表 2星图去噪前后的MSE对比
Table 2.Comparison of MSE values of star images before and after denoising
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表 3顶帽变换和阈值处理前后星图的MSE对比
Table 3.Comparison of MSE values of the images before and after Top-hat transform and threshold processing
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表 4对含σ=0.01高斯噪声的星图质心提取结果
Table 4.Results of the star image centroid extraction withσ=0.01 Gaussian noise
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表 5对含σ=0.1高斯噪声的星图质心提取结果
Table 5.Results of the star image centroid extraction withσ=0.1 Gaussian noise
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