Clustering SPIHT output bits for wireless communications

Fang, Jiunn-Tsair; Shyu, Woei-Luen; Wu, Cheng-Shong

doi:10.1049/el:20030175

Cited by 6 publications

(7 citation statements)

References 4 publications

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“…It clusters SPIHT output bits and also enhances the error-resilience. For more information about the algorithms of SPIHT and C-SPIHT, please refer to [16,4], respectively.…”

Section: C-spihtmentioning

confidence: 99%

“…On the other hand, any decoded error on sign bits or magnitude bits affects only the resolution of one pixel. Thus, significance bits are more important than sign bits or magnitude bits [4].…”

Section: The Bes Of O-spihtmentioning

confidence: 99%

“…[13]. Since the fixed-length coding format is used for LOP-M and LOP-S, the high BES of significant pixel bits are not required and the error resilience of C-SPIHT is improved [4].…”

Section: The Bes Of O-spihtmentioning

confidence: 99%

“…C-SPIHT is a modified version of SPIHT for wireless communications [4]. It not only clusters SPIHT output bits, but also enhances the error-resilience of SPIHT.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Clustering source output bits and equalizing bit error sensitivity to improve the quality and robustness of transmitted images over wireless channels

Fang

Shyu

et al. 2003

Signal Processing: Image Communication

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“…It clusters SPIHT output bits and also enhances the error-resilience. For more information about the algorithms of SPIHT and C-SPIHT, please refer to [16,4], respectively.…”

Section: C-spihtmentioning

confidence: 99%

Section: The Bes Of O-spihtmentioning

confidence: 99%

“…[13]. Since the fixed-length coding format is used for LOP-M and LOP-S, the high BES of significant pixel bits are not required and the error resilience of C-SPIHT is improved [4].…”

Section: The Bes Of O-spihtmentioning

confidence: 99%

“…C-SPIHT is a modified version of SPIHT for wireless communications [4]. It not only clusters SPIHT output bits, but also enhances the error-resilience of SPIHT.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Clustering source output bits and equalizing bit error sensitivity to improve the quality and robustness of transmitted images over wireless channels

Fang

Shyu

et al. 2003

Signal Processing: Image Communication

Self Cite

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“…In particular, C-SPIHT is suitable for the application of wireless communications because it is convenient for the design of the method of unequal error protection (UEP). 12 To further improve the transmission quality, we classify C-SPIHT output bit clusters. In principle, bit clusters with higher average BESs, which can tolerate less error bits, have a higher number of iterations.…”

Section: Introductionmentioning

confidence: 99%

Dynamic stopping criteria of turbo codes for clustered set partitioning in hierarchical trees encoded image transmission

Fang

2011

J. Electron. Imaging

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Turbo codes adopt iterative decoding to increase the ability of error correction. However, the iterative method increases the decoding delay and power consumption. An effective approach is to decrease the number of iterations while tolerating slight performance degradation. We apply the clustered set partitioning in hierarchical trees for image coding. Different from other early stop criteria, we use the bit-error sensitivities from the image data. Then, the stop criterion is directly determined by the importance of image data. Simulation results show that our scheme can reduce more number of iterations with less degradation for peak-signal-to-noise ratio or structure similar performance.

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