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词典学习与天文图像恢复Dictionary Learning and Astronomical Image Restoration |
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| 课程网址: | http://videolectures.net/nipsworkshops2011_beckouche_learning/ |
| 主讲教师: | Simon Beckouche |
| 开课单位: | 法国替代能源和原子能委员会 |
| 开课时间: | 2012-06-23 |
| 课程语种: | 汉简 |
| 中文简介: |  |
| 课程简介: | Wavelets have been intensely used for astronomical image restoration during the last 20 years. However, wavelets have shown some limitations for images containing complexe texture features that can find in cosmic string maps or planetary images. We propose to use recently developed dictionary learning techniques to overcome those limitations. We address here the problem where a white gaussian noise is to be removed from an image. The original image is assumed to be sparsly represented in a dictionary which is learned during the denoising. Patch averaging has proven to be an efficient way to combine local sparsity constrain and a global Bayesian treatment and is applied here to process astrophysical image compared to classic wavelet shrinkage and associated techniques. |
| 关 键 词: | 天文图像; 斑块平均; 高斯白噪声 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2020-11-30：yxd |
| 最后编审: | 2020-11-30：yxd |
| 阅读次数: | 28 |