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给出了一种特别适合于低功耗硬件实现的运动和图像特征自适应的块匹配运动估值算法 ,它采用一种新的由运动跟踪搜索和望远镜搜索组成的两阶段可提前中断的搜索方法 ,根据宏块的运动特征和图像特征自适应地控制中断、调整搜索窗的大小和改变像素数据的表示精度。模拟结果表明新算法的平均运算量仅为传统算法的 30 %～ 40 %左右 ,却可以得到与传统算法相同的视频解码图质量。一种一维心动阵列保证了这一新算法的低功耗硬件实现
A block matching motion estimation algorithm is proposed, which is especially suitable for motion and image feature adaptation implemented by low-power hardware. It uses a new two-phase pre-emptive search that consists of motion tracking search and telescope search The method adaptively controls the interrupt according to the motion features and the image features of the macro block, adjusts the size of the search window and changes the representation accuracy of the pixel data. The simulation results show that the average computational complexity of the new algorithm is only about 30% ~ 40% of that of the traditional one, but the quality of the same video decoding scheme can be obtained. A one-dimensional cardiac array ensures low-power hardware implementation of this new algorithm