DCT-based video downscaling transcoder using split and merge technique.
For a conventional downscaling video transcoder, a video server has firstly to decompress the video, perform downscaling operations in the pixel domain, and then recompress it. This is computationally intensive. However, it is difficult to perform video downscaling in the discrete cosine transform (DCT)- domain since the prediction errors of each frame are computed from its immediate past higher resolution frames. Recently, a fast algorithm for DCT domain image downsampling has been proposed to obtain the downsampled version of DCT coefficients with low computational complexity. However, there is a mismatch between the downsampled version of DCT coefficients and the resampled motion vectors. In other words, significant quality degradation is introduced when the derivation of the original motion vectors and the resampled motion vector is large. In this paper, we propose a new architecture to obtain resampled DCT coefficients in the DCT domain by using the split and merge technique. Using our proposed video transcoder architecture, a macroblock is splitted into two regions: dominant region and the boundary region. The dominant region of the macroblock can be transcoded in the DCT domain with low computational complexity and re-encoding error can be avoided. By transcoding the boundary region adaptively, low computational complexity can also be achieved. More importantly, the re-encoding error introduced in the boundary region can be controlled more dynamically. Experimental results show that our proposed video downscaling transcoder can lead to significant computational savings as well as videos with high quality as compared with the conventional approach. The proposed video transcoder is useful for video servers that provide quality service in real-time for heterogeneous clients.
Centre for Multimedia Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong. enktfung@eie.polyu.edu.hk
Kai-Tat
KT
Fung
Wan-Chi
WC
Siu
D000465:Algorithms; D003195:Computer Communication Networks; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D014741:Video Recording / Q000379:methods*