Down-sampling design in DCT domain with arbitrary ratio for image/video transcoding.
This paper proposes a designing framework for down-sampling compressed images/video with arbitrary ratio in the discrete cosine transform (DCT) domain. In this framework, we first derive a set of DCT-domain down-sampling methods which can be represented by a linear transform with double-sided matrix multiplication (LTDS) in the DCT domain and show that the set contains a wide range of methods with various complexity and visual quality. Then, for a preselected spatial-domain down-sampling method, we formulate an optimization problem for finding an LTDS to approximate the given spatial-domain down-sampling method for a trade-off between the visual quality and the complexity. By modeling LTDS as a multiple layer network, a so-called structural learning with forgetting algorithm is then applied to solve the optimization problem. The proposed framework has been applied to discover optimal LTDSs corresponding to a spatial down-sampling method with Butterworth low-pass filtering and bicubic interpolation. Experimental results show that the resulting LTDS achieves a significant reduction on the complexity when compared with other methods in the literature with similar visual quality.
Yu
Xiang
X
Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario, Canada. xiayu@rim.com
Yang
En-hui
EH
Wang
Haiquan
H
D000465:Algorithms; D044962:Data Compression / Q000379:methods*; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D014741:Video Recording / Q000379:methods*