Assorted pixels: multi-sampled imaging with structural models
Assorted pixels: multi-sampled imaging with structural models
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分类像素：具有结构模型的多采样成像
DOI：
10.1145/1185657.1185743
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发表时间：
2005
期刊：
影响因子：
--
通讯作者：
S. Narasimhan
中科院分区：
文献类型：
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作者：
S. Nayar;S. Narasimhan
多采样成像是使用图像探测器上的像素同时对成像的多个维度（空间、时间、光谱、亮度、偏振等）进行采样的通用框架。大多数固态彩色相机中的红色、绿色和蓝色光谱滤光片镶嵌是多采样成像的一个例子。我们简要描述了如何使用多重采样来探索成像的其他维度。一旦捕获了这样的图像，就可以使用标准插值算法获得沿各个维度的平滑重建。通常，这会导致分辨率（以及图像质量）大幅下降。通过注意到与真实场景相关的光场内部具有巨大的冗余，导致不同的维度高度相关，人们可以在每个维度中提取显着更高的分辨率。因此，使用从不同的训练图像集中离线学习的局部结构模型可以更好地对多采样图像进行插值。我们使用的特定类型的结构模型基于测量图像强度的多项式函数。它们非常有效并且计算效率很高。我们使用三个特定应用程序展示了结构插值的好处。它们是（a）使用彩色滤光片马赛克的传统彩色成像，（b）使用曝光滤光片马赛克的高动态范围单色成像，以及（c）使用重叠颜色和曝光滤光片马赛克的高动态范围彩色成像。
Multi-sampled imaging is a general framework for using pixels on an image detector to simultaneously sample multiple dimensions of imaging (space, time, spectrum, brightness, polarization, etc.). The mosaic of red, green and blue spectral filters found in most solid-state color cameras is one example of multi-sampled imaging. We briefly describe how multi-sampling can be used to explore other dimensions of imaging. Once such an image is captured, smooth reconstructions along the individual dimensions can be obtained using standard interpolation algorithms. Typically, this results in a substantial reduction of resolution (and hence image quality). One can extract significantly greater resolution in each dimension by noting that the light fields associated with real scenes have enormous redundancies within them, causing different dimensions to be highly correlated. Hence, multi-sampled images can be better interpolated using local structural models that are learned off- line from a diverse set of training images. The specific type of structural models we use are based on polynomial functions of measured image intensities. They are very effective as well as computationally efficient. We demonstrate the benefits of structural interpolation using three specific applications. These are (a) traditional color imaging with a mosaic of color filters, (b) high dynamic range monochrome imaging using a mosaic of exposure filters, and (c) high dynamic range color imaging using a mosaic of overlapping color and exposure filters.