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首页> 外文期刊>Journal of Real-Time Image Processing >Entire frame image display employing monotonic convergent nonnegative matrix factorization
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Entire frame image display employing monotonic convergent nonnegative matrix factorization

机译:使用单调收敛非负矩阵分解的全帧图像显示

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The average life spans of light-emitting diodes (LEDs) used in organic light-emitting diode displays are negatively influenced by high current operation in short duty cycles. Since the time average brightness of a pixel LED is a function only of the time integral of the delivered current, it is desirable to achieve brightness by adopting pixel addressing schemes that employ long duty cycles. Conventional addressing methods which cannot operate more than one row of pixels at a time inherently have very short duty cycles. We solve the problem by proposing entire frame addressing, made possible by a new image factorization called monotonic-nonnegative matrix factorization (M-NNMF). Using M-NNMF, we develop a converging image series representation of an arbitrary nonnegative matrix (image). Each element of the series has unit rank, which allows it to drive an entire frame simultaneously. Each application of the M-NNMF algorithm produces a dominant unit rank component for the series, and a residue image of higher rank, the input to the next iteration. We drive the display with these unit rank components, called sub-frames, each for a duration proportional to its energy. The sum of sub-frames approximates the original image and provides the same visual effect, due to inherent perceptual integration. M-NNMF, more efficient and less time complex compared to existing NNMF algorithms, is our primary contribution in this paper and is likely to find applications in many other situations. We also obtain an even faster converging series with a randomized version of M-NNMF. The proposed approach of entire frame image display is demonstrated on a wide variety of images.
机译:有机发光二极管显示器中使用的发光二极管(LED)的平均寿命受到短占空比高电流操作的负面影响。由于像素LED的时间平均亮度仅是所输送电流的时间积分的函数,因此希望通过采用采用长占空比的像素寻址方案来获得亮度。一次不能操作多于一行像素的常规寻址方法固有地具有非常短的占空比。我们通过提出整个帧寻址来解决该问题,这可以通过称为单调非负矩阵分解(M-NNMF)的新图像分解来实现。使用M-NNMF,我们开发了任意非负矩阵(图像)的会聚图像序列表示。该系列的每个元素都有单位等级,这使其可以同时驱动整个框架。 M-NNMF算法的每个应用程序都会生成该序列的主要单位等级分量,以及更高等级的残差图像,这是下一次迭代的输入。我们使用这些称为子帧的单位等级组件驱动显示,每个组件的持续时间与其能量成正比。由于固有的感知整合,子帧的总和近似于原始图像并提供相同的视觉效果。与现有的NNMF算法相比,M-NNMF更高效,更省时,是我们在本文中的主要贡献,并且有可能在许多其他情况下找到应用。我们还使用M-NNMF的随机版本获得了更快的收敛级数。所提出的全帧图像显示方法在各种图像上得到了证明。

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