为了提升可分级视频编码的层间帧内预测(ILIP)性能,提出了一种基于维纳滤波器的块级别自适应ILIP方法.首先,将一帧图像分块;其次,逐块选取原始增强层图像和对应的基本层上采样图像逐帧进行训练,得到维纳滤波器系数;最后,采用获取的滤波器系数对基本层上的采样图像进行滤波,并在块级别加以控制,以便降低预测误差能量.实验结果表明,与传统ILIP方法相比,新方法可以获得更精确的预测结果,编码器输出比特率下降最高可达14.45%. In order to improve the inter-layer intra prediction (ILIP) performance of scalable video coding, a Wiener filter-based block-level adaptive ILIP method is proposed. First, one frame of image is segmented. Secondly, the original enhancement Layer images and the corresponding base layer upsampled images to obtain the Wiener filter coefficients; finally, the obtained filter coefficients are used to filter the sampled images in the base layer and controlled at the block level in order to reduce the prediction Error energy.The experimental results show that the new method can get more accurate prediction results than the traditional ILIP method and the output bit rate of the encoder can drop by up to 14.45%.