Fast and robust fixed-length packetization algorithm for set partitioning in hierarchical trees bit stream over packet erasure channels

2007 ◽  
Vol 16 (1) ◽  
pp. 013007
Author(s):  
Jianming Wei
Keyword(s):  
Set Partitioning ◽  
Erasure Channels ◽  
Fixed Length ◽  
Hierarchical Trees ◽  
Bit Stream

scholarly journals Set Partitioning in Hierarchical Trees for Point Cloud Attribute Compression

2021 ◽  
Author(s):  
Ricardo de Queiroz ◽  
Andre Souto ◽  
Victor Figueiredo ◽  
Philip Chou
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
Set Partitioning ◽  
Hierarchical Trees ◽  
Standard Geometry ◽  
Encoding Method ◽  
Bit Stream

<div>We propose an embedded attribute encoding method for point clouds based on set partitioning in hierarchical trees (SPIHT) [1]. The encoder is used with the region-adaptive hierarchical transform [2] which has been a popular transform for point cloud coding, even included in the standard geometry-based point cloud coder (G-PCC) [3],[4]. The result is an encoder that is efficient, scalable, and embedded. That is, higher compression is achieved by trimming the full bit-stream. G-PCC’s RAHT coefficient prediction prevents the straightforward incorporation of SPIHT into G-PCC. However, our results over other RAHT based coders are promising, improving over the original, nonpredictive RAHT encoder, while providing the key functionality of being embedded.</div>

scholarly journals Set Partitioning in Hierarchical Trees for Point Cloud Attribute Compression

2021 ◽  
Author(s):  
Ricardo de Queiroz ◽  
Andre Souto ◽  
Victor Figueiredo ◽  
Philip Chou
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
Set Partitioning ◽  
Hierarchical Trees ◽  
Standard Geometry ◽  
Encoding Method ◽  
Bit Stream

<div>We propose an embedded attribute encoding method for point clouds based on set partitioning in hierarchical trees (SPIHT) [1]. The encoder is used with the region-adaptive hierarchical transform [2] which has been a popular transform for point cloud coding, even included in the standard geometry-based point cloud coder (G-PCC) [3],[4]. The result is an encoder that is efficient, scalable, and embedded. That is, higher compression is achieved by trimming the full bit-stream. G-PCC’s RAHT coefficient prediction prevents the straightforward incorporation of SPIHT into G-PCC. However, our results over other RAHT based coders are promising, improving over the original, nonpredictive RAHT encoder, while providing the key functionality of being embedded.</div>

A Novel Layered Error Resilient Method for SPIHT-Coded Images over Packet Networks

2011 ◽  
Vol 204-210 ◽  
pp. 964-968
Author(s):  
Wen Zhu Sun ◽  
Hong Yu Wang ◽  
Jie Wang
Keyword(s):  
Set Partitioning ◽  
Packet Networks ◽  
Data Partition ◽  
Error Resilient ◽  
Erasure Channels ◽  
Multiple Description ◽  
Hierarchical Trees ◽  
Bit Planes ◽  
Spiht Coding ◽  
Coded Images

This paper presents a layered error resilient scheme for Set Partitioning in Hierarchical Trees (SPIHT) coding which incorporates the Multiple Description Coding (MDC) into the data partition. The major feature of this scheme is that the MDC is adopted in the process of packetizing the spatial orientation trees, so as to protect the important information bits according to different importance and channel state. The proposed scheme can allocate redundancy accurately and flexibly, by differentiating importance of bits through different bit planes. Experimental results show that the proposed method achieves good performance over packet erasure channels.

scholarly journals High Rate Squeezing using LL Band Coding in Wavelet Domain

2019 ◽  
Vol 8 (6S) ◽  
pp. 102-111
Keyword(s):  
Set Partitioning ◽  
High Rate ◽  
Similar Process ◽  
Wavelet Domain ◽  
Wavelet Theory ◽  
Cost Of Quality ◽  
Processing Task ◽  
Hierarchical Trees ◽  
Application Fields ◽  
Spiht Coding

Wavelet based image compression standards not only inspired signal and image processing community but also the research community of many research and application fields towards the wavelet theory. All wavelet based schemes follow the standard sequence of steps. They are transformation and the processing task at one end followed by the inverse of processing task and inverse transform at another end. Wavelet based compression was done in a quite different manner from its inception. The early techniques include Embedded Zerotree Wavelet (EZW) coding and Set Partitioning in Hierarchical Trees (SPIHT) coding. Although, SPIHT is an extension of EZW, both follow more or less similar process in coding and decoding. These schemes code the significant and insignificant coefficients using symbols or maintaining a list of indices of the coefficients. The decision on significant or insignificant will be taken by comparing with a threshold which will be updated in each iteration. In both the schemes, if a coefficient is identified as an insignificant one, then the bits incurred in conveying this coefficient is less and in many cases very less. One can imagine that if a coefficient is made to be an insignificant then the number of bits required will be less. This issue was taken up in this paper and bits of selected regions is chosen and a significant improvement is compression ratio is observed at a little cost of quality.

scholarly journals A Very Compact AES-SPIHT Selective Encryption Computer Architecture Design with Improved S-Box

2013 ◽  
Vol 2013 ◽  
pp. 1-26 ◽  
Author(s):  
Jia Hao Kong ◽  
Li-Minn Ang ◽  
Kah Phooi Seng
Keyword(s):  
Computer Architecture ◽  
Nonlinear Property ◽  
Set Partitioning ◽  
Advanced Encryption Standard ◽  
Instruction Set ◽  
Selective Encryption ◽  
Low Area ◽  
Gate Count ◽  
Hierarchical Trees ◽  
Spiht Algorithm

The “S-box” algorithm is a key component in the Advanced Encryption Standard (AES) due to its nonlinear property. Various implementation approaches have been researched and discussed meeting stringent application goals (such as low power, high throughput, low area), but the ultimate goal for many researchers is to find a compact and small hardware footprint for the S-box circuit. In this paper, we present our version of minimized S-box with two separate proposals and improvements in the overall gate count. The compact S-box is adopted with a compact and optimum processor architecture specifically tailored for the AES, namely, the compact instruction set architecture (CISA). To further justify and strengthen the purpose of the compact crypto-processor’s application, we have also presented a selective encryption architecture (SEA) which incorporates the CISA as a part of the encryption core, accompanied by the set partitioning in hierarchical trees (SPIHT) algorithm as a complete selective encryption system.

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