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为改善动态伪轮廓(DFC)及其引起的灰度级损失,提出一种基于行内运动图像干扰(MPD)极值的自适应子场编码方法。该方法通过计算一行图像内出现的DFC极大值及其位置变化判断图像运动状态,再根据图像不同运动状选择DFC极小的灰度编码。对静态图像采用无灰度级损失的全灰阶编码方式,对动态图像采用DFC极小的关键灰度级编码。该方法的运动状态判断和关键灰度级选择均基于行图像的MPD极值完成,实验结果表明:静态图像显示细节丰富完整,动态图像DFC可减轻30%。
In order to improve the dynamic false contour (DFC) and the grayscale loss caused by it, an adaptive sub-field coding method based on the extreme value of in-line motion image interference (MPD) is proposed. The method determines the motion state of the image by calculating the maximum value of DFC and its position in a row of images, and then selects the minimum gray coding of DFC according to the different motion of the image. For the static image, the whole grayscales with no grayscale loss are adopted, and the key grayscale codes with the smallest DFC are used for the moving images. The determination of the motion state and the selection of the key grayscale of the method are all based on the MPD extreme value of the line image. The experimental results show that the static image display details are rich and complete, and the dynamic image DFC can be reduced by 30%.