Stability study of the SB-ADPCM coder
Signal Processing
Low-complexity and energy efficient image compression scheme for wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Filter banks for prediction-compensated multiple description coding
IEEE Transactions on Signal Processing
On the arbitrary-length M-channel linear phase perfect reconstruction filter banks
IEEE Transactions on Signal Processing
Multiple description coding with prediction compensation
IEEE Transactions on Image Processing
Efficient block-based frequency domain wavelet transform implementations
IEEE Transactions on Image Processing
Time-varying cosine-modulated filter banks
Digital Signal Processing
Image compression with downsampling and overlapped transform at low bit rates
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Directional lapped transforms for image coding
IEEE Transactions on Image Processing
DFT spectrum estimation from critically sampled lapped transforms
Signal Processing
A two-channel overlapped block transform for image compression
IEEE Transactions on Image Processing
Stabilization and optimization of PLUS factorization and its application in image coding
Journal of Visual Communication and Image Representation
A three-layer scheme for M-channel multiple description image coding
Signal Processing
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This paper presents a general framework of constructing a large family of lapped transforms with symmetric basis functions by adding simple time-domain pre- and post-processing modules onto existing block discrete cosine transform (DCT)-based infrastructures. A subset of the resulting solutions is closed-form, fast computable, modular, near optimal in the energy compaction sense and leads to an elegant boundary handling of finite-length data. Starting from these solutions, a general framework for block-based signal decomposition with a high degree of flexibility and adaptivity is developed. Several simplified models are also introduced to approximate the optimal solutions. These models are based on cascades of plane rotation operators and lifting steps, respectively. Despite tremendous savings in computational complexity, the optimized results of these simplified models are virtually identical to that of the complete solution. The multiplierless versions of these pre- and post-filters when combined with an appropriate multiplierless block transform, such as the binDCT, which is described in an earlier paper by Liang and Tran (see IEEE Trans. Signal Processing, vol.49, p.3032-44, Dec. 2001), generate a family of very large scale integration (VLSI)-friendly fast lapped transforms with reversible integer-to-integer mapping. Numerous design examples with arbitrary number of channels and arbitrary number of borrowed samples are presented.