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SPIHT Algorithm With Adaptive Selection of Compression Ratio Depending on DWT Coefficients
- Source :
- IEEE Transactions on Multimedia. 20:3200-3211
- Publication Year :
- 2018
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2018.
-
Abstract
- In mobile multimedia devices, the frame memory compression (FMC) technique by embedded compression (EC) is becoming an increasingly important video-processing method for reducing the external data bandwidth requirement, which, in turn, results in power savings. Among various EC schemes, the combination of discrete wavelet transform (DWT) and set partitioning in hierarchical trees (SPIHT) is widely used for FMC because it achieves high compression efficiency with low computational complexity. However, there is room for improvement in the conventional DWT and SPIHT algorithm because it compresses all blocks with the same compression ratio without taking into account the correlation between DWT coefficients and the SPIHT algorithm. This study proposes a novel one-dimensional (1-D) DWT and SPIHT algorithm, which enhances the quality of the compressed video by internally applying an adaptive compression ratio for the SPIHT algorithm based on DWT coefficients while keeping the same bit-stream size. The block complexity is predicted from the distribution of DWT coefficients. Then, simple blocks are aggressively compressed with a low compression ratio, while the complex blocks are compressed with a high ratio. Furthermore, to achieve the best video quality, each compression ratio is decided by an optimization technique based on mathematical formulation. Precisely, the logarithm of mean squared error by the SPIHT algorithm is assumed to be linearly correlated with the logarithm of processed DWT coefficients. Experimental results are provided that support the aforementioned model. Compared to the conventional 1-D DWT and SPIHT algorithm, the proposed scheme remarkably improves the video quality by an average of 2.23 dB in peak signal-to-noise ratio when the target compression ratio for the SPIHT algorithm is 5/16.
- Subjects :
- Discrete wavelet transform
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
020206 networking & telecommunications
Data_CODINGANDINFORMATIONTHEORY
02 engineering and technology
Video quality
Computer Science Applications
Set partitioning in hierarchical trees
Adaptive compression
Signal Processing
Compression ratio
0202 electrical engineering, electronic engineering, information engineering
Media Technology
020201 artificial intelligence & image processing
Electrical and Electronic Engineering
Algorithm
Block (data storage)
Subjects
Details
- ISSN :
- 19410077 and 15209210
- Volume :
- 20
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Multimedia
- Accession number :
- edsair.doi...........01a601978d93ab0f4194415cb44acb04