Mehrseresht Nagita, Taubman David
School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney, Australia.
IEEE Trans Image Process. 2006 Jun;15(6):1397-412. doi: 10.1109/tip.2005.864236.
We propose a novel, content adaptive method for motion-compensated three-dimensional wavelet transformation (MC 3-D DWT) of video. The proposed method overcomes problems of ghosting and nonaligned aliasing artifacts which can arise in regions of motion model failure, when the video is reconstructed at reduced temporal or spatial resolutions. Previous MC 3-D DWT structures either take the form of MC temporal DWT followed by a spatial transform ("t+2D"), or perform the spatial transform first ("2D + t"), limiting the spatial frequencies which can be jointly compensated in the temporal transform, and hence limiting the compression efficiency. When the motion model fails, the "t + 2D" structure causes nonaligned aliasing artifacts in reduced spatial resolution sequences. Essentially, the proposed transform continuously adapts itself between the "t + 2D" and "2D + t" structures, based on information available within the compressed bit stream. Ghosting artifacts may also appear in reduced frame-rate sequences due to temporal low-pass filtering along invalid motion trajectories. To avoid the ghosting artifacts, we continuously select between different low-pass temporal filters, based on the estimated accuracy of the motion model. Experimental results indicate that the proposed adaptive transform preserves high compression efficiency while substantially improving the quality of reduced spatial and temporal resolution sequences.
我们提出了一种新颖的、内容自适应的视频运动补偿三维小波变换（MC 3-D DWT）方法。当视频以降低的时间或空间分辨率重建时，该方法克服了运动模型失效区域可能出现的重影和未对齐的混叠伪像问题。以前的MC 3-D DWT结构要么采用先进行MC时间DWT再进行空间变换的形式（“t + 2D”），要么先进行空间变换（“2D + t”），这限制了在时间变换中可以联合补偿的空间频率，从而限制了压缩效率。当运动模型失效时，“t + 2D”结构会在降低空间分辨率的序列中导致未对齐的混叠伪像。本质上，所提出的变换基于压缩比特流中可用的信息，在“t + 2D”和“2D + t”结构之间不断自适应调整。由于沿着无效运动轨迹的时间低通滤波，重影伪像也可能出现在降低帧率的序列中。为了避免重影伪像，我们根据运动模型的估计精度，在不同的低通时间滤波器之间不断进行选择。实验结果表明，所提出的自适应变换在保持高压缩效率的同时，显著提高了降低空间和时间分辨率序列的质量。
