基于自适应卡尔曼的时域增强算法研究

Research on time domain enhancement algorithm based on adaptive Kalman filter

在图像序列进行压缩感知重构的过程中,基于运动补偿的分块压缩感知重建算法利用了帧间残差图像的稀疏特性,有效提高了重构视频的质量。但该算法仅在空域对图像进行了维纳滤波,帧间存在抖动现象,视频主观质量较差。文章将自适应卡尔曼滤波算法应用到分块压缩感知重建算法的重建过程中,可以有效地去除视频帧间的噪声,使得图像的主观质量得到了改善。

In the process of compressed sensing reconstruction for image sequence,block compressed sensing reconstruction algorithm based on the motion compensation effectively improved the quality of the reconstructed video frames by utilizing the characteristics of inter sparse residual image. But this algorithm just utilized Wiener filtering in the spatial domain, and for the inter jitter existed, the reconstructed video frames had a little bit poor subjective quality. In this paper,an adaptive Kalman filter algorithm is applied to block compressed sensing reconstruction algorithm in the reconstruction process,which effectively removes the noise between image frames and makes better subjective quality.