农业图像去噪算法研究

Research on Agricultural Image Denoising Algorithm

受外界因素影响,获得的农业图像经常含有噪声,影响后续分析。基于此,提出一种基于剪切波(Shearlets)变换的农业图像去噪算法,Shearlets变换具有灵活的方向选择性,易于实现,克服了小波变换在去噪方面的不足。利用本算法与传统的小波去噪算法对农业图像进行测试、对比,评价指标采用峰值信噪比来客观评价去噪算法性能。实验结果表明,该算法的去噪效果优于传统小波算法,可推广运用到农业图像去噪实践中。

Affected by external factors,the obtained agricultural images often contain noise,which affects subsequent analysis.In this paper,an agricultural image denoising algorithm based on Shearlets transform is proposed.Shearlets transform has flexible direction selectivity and is easy to implement,which overcomes the shortcomings of wavelet transform in denoising.The agricultural images are tested and compared with the traditional wavelet denoising algorithm,and the peak signal noise to ratio is used as the objective evaluation index of the performance of the denoising algorithm.The experimental results show that the denoising effect of the algorithm is better than the traditional wavelet algorithm,which can be applied to the practice of agricultural image denoising.