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CONVERGENT MONOTONIC MATRIX FACTORIZATION BASED ENTIRE FRAME IMAGE PROCESSING

机译:基于融合单调矩阵分解的全帧图像处理

摘要

Technologies are generally described for the display of images by employing monotonic matrix factorization and sub-frame approximation image integration. In some examples, drive signals for a display device may be generated by iteratively applying a monotonic non-negative matrix factorization (NNMF) process to source image data. A given iteration of the monotonic NNMF process may result in approximation image data, partial sum image data, and residue image data, some or all of which may be further processed via subsequent iterations of the monotonic NNMF process. A generated approximation image data may then be displayed during a sub-frame time interval by selective activation of multiple row and column drivers. A series of such displayed approximation image data may effectively correspond to the original source image. In particular, the monotonic NNMF process may allow the generation of non-negative residue image data without the use of element reduction.
机译:通常描述了通过采用单调矩阵分解和子帧近似图像积分来显示图像的技术。在一些示例中,可以通过将单调非负矩阵分解(NNMF)过程迭代地应用于源图像数据来生成用于显示设备的驱动信号。单调NNMF过程的给定迭代可以产生近似图像数据,部分和图像数据和残差图像数据,其中一些或全部可以通过单调NNMF过程的后续迭代来进一步处理。然后,可以通过选择性地激活多个行和列驱动器来在子帧时间间隔期间显示所生成的近似图像数据。一系列这样显示的近似图像数据可以有效地对应于原始源图像。特别地,单调NNMF过程可以允许在不使用元素缩减的情况下生成非负残留图像数据。

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