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为改善“累积”发光驱动方法显示静态图像时的灰度级轮廓,提出了一种基于有效灰度级均匀分割采样的动态子场编码(DSC)算法。首先对输入图像中的孤立灰度区间进行灰度采样,然后对剩余灰度级均匀分割,选择各灰度区间概率密度较大的灰度级作为采样灰度级,相邻采样灰度级之差即为子场编码权值,从而使采样灰度级均匀分布在输入图像的有效灰度区间,并使采样灰度级和子场编码权值随图像变化。仿真和实验结果表明,该算法不仅能真实再现大面积的背景,而且使图像细节信息尽可能保留,显著减小了静态图像的轮廓。
In order to improve the grayscale contour of the “Accumulate” LED display method when displaying static images, a dynamic sub-field coding (DSC) algorithm based on uniform grayscale sampling of effective grayscale is proposed. Firstly, gray-scale sampling is performed on the isolated gray-level intervals in the input image, then the remaining gray-level is evenly divided, and the gray-scale with the higher probability density in each gray-level interval is selected as the sampling gray-level and the adjacent sampling gray-scale The difference is the coding weight of the subfield, so that the sampling gray level is evenly distributed in the effective gray interval of the input image, and the sampling gray level and the weight of the subfield coding vary with the image. Simulation and experimental results show that the proposed algorithm not only reproduces the large area background but also preserves the image details as much as possible and reduces the contour of the static image significantly.