图 书 馆
采样图像在时间和空间的代码Codes for Sampling Images over Time and Space |
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| 课程网址: | http://videolectures.net/nipsworkshops2010_freeman_csi/ |
| 主讲教师: | William T. Freeman |
| 开课单位: | 麻省理工学院 |
| 开课时间: | 2011-01-12 |
| 课程语种: | 英语 |
| 中文简介: | 人类视觉系统和几乎每个数码相机都通过使用以某种空间模式排列的不同光谱灵敏度的传感器来实现三色性。什么样的空间采样最好？我将描述有关学习最佳（好的，局部最佳）滤色器阵列的工作。这种学习的采样模式比拜耳模式和许多其他模式更好地重建彩色图像。如果有时间，我会谈谈一段时间内采样的一些问题，并显示可以在像素强度计数器中加减的相机的模拟结果。 |
| 课程简介: | The human visual system, and almost every digital camera, achieves trichromacy by using sensors of different spectral sensitivity arranged in some spatial pattern. What pattern of spatial sampling is best? I’ll describe work on learning an optimal (ok, locally optimal) color filter array. This learned sampling pattern leads to better reconstructions of color images than the Bayer pattern and many others. If there is time, I’ll talk about some issues in sampling over time, and show simulation results for a camera that can both add and subtract from a pixel intensity counter. |
| 关 键 词: | 视觉系统; 光谱灵敏度; 拜耳模式 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-06：毛岱琦(课程编辑志愿者) |
| 阅读次数: | 48 |