精品文档---下载后可任意编辑高光谱图像条带噪声去除方法讨论与应用的开题报告摘要高光谱图像是一种蕴含多光谱信息的图像，具有广泛的应用前景。然而，高光谱图像往往受到条带噪声的影响，影响图像质量和准确性。因此，本文旨在讨论高光谱图像条带噪声去除方法，并应用于实际数据中。本文首先介绍高光谱图像及其应用场景，然后详细分析高光谱图像条带噪声的特点和成因。接着，对于目前的条带噪声去除方法进行了综述和评估。在此基础上，本文提出了一种基于小波变换和均值滤波的条带噪声去除方法，并进行了实验验证。实验结果表明，本文提出的方法在去除高光谱图像条带噪声方面具有较好效果。同时，本文探讨了方法的适用性和不足之处，并提出了改进方向。关键词：高光谱图像，条带噪声，小波变换，均值滤波AbstractHyperspectral imaging is an image containing multispectral information, with wide application prospects. However, hyperspectral images are often affected by stripe noise, which affects image quality and accuracy. Therefore, this paper aims to study the method of stripe noise removal in hyperspectral images and apply it to actual data.This paper first introduces hyperspectral imaging and its application scenarios, and then analyzes the characteristics and causes of stripe noise in hyperspectral images in detail. Then, the current methods for stripe noise removal are reviewed and evaluated. Based on this, this paper proposes a stripe noise removal method based on wavelet transform and mean filtering, and conducts experimental verification.The experimental results show that the method proposed in this paper has a good effect in removing stripe noise in hyperspectral images. At the same time, this paper discusses the applicability and shortcomings of the method and proposes improvement directions.Keywords: hyperspectral imaging, stripe noise, wavelet transform, mean filtering
