A full-featured, error-resilient, scalable wavelet video codec based on the set partitioning in hierarchical trees (SPIHT) algorithm

2002 ◽  
Vol 12 (3) ◽  
pp. 157-171 ◽  
Author(s):  
Sungdae Cho ◽  
W.A. Pearlman
Keyword(s):  
Set Partitioning ◽  
Video Codec ◽  
Error Resilient ◽  
Hierarchical Trees ◽  
Spiht Algorithm

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.

BINARY TREE IMAGE CODING ALGORITHM BASED ON NON-SEPARABLE WAVELET TRANSFORM VIA LIFTING SCHEME

2008 ◽  
Vol 06 (05) ◽  
pp. 761-775 ◽  
Author(s):  
CHENG-YOU WANG ◽  
ZHENG-XIN HOU ◽  
AI-PING YANG
Keyword(s):  
Wavelet Transform ◽  
Image Coding ◽  
Binary Tree ◽  
Lifting Scheme ◽  
Set Partitioning ◽  
Interpolation Filter ◽  
Hierarchical Trees ◽  
Spiht Algorithm ◽  
Phase Interpolation ◽  
Tree Image

In recent years, image coding based on wavelet transform has made rapid progress. In this paper, quincunx lifting scheme in wavelet transform is introduced and all phase interpolation filter banks which can be used in the lifting scheme for prediction and update are designed. Based on the basic idea of set partitioning in hierarchical trees (SPIHT) algorithm, the binary tree image coding algorithm is proposed. Just like SPIHT, the encoding algorithms can be stopped at any compressed file size or let run until the compressed file is a representation of a nearly lossless image. The experimental results on test images show that compared with SPIHT algorithm, the PSNRs of the proposed algorithm are superior by about 0.5 dB at the same bit rates and the subjective quality of reconstructed images is also better.

NEW SPIHT-BASED ALGORITHM FOR ELECTROCARDIOGRAM SIGNAL COMPRESSION

2019 ◽  
Vol 19 (03) ◽  
pp. 1950005
Author(s):  
ABDELNOUR BOUKAACHE ◽  
NOUREDDINE DOGHMANE ◽  
DJALIL BOUDJEHEM
Keyword(s):  
Original Method ◽  
Numerical Results ◽  
Set Partitioning ◽  
Ecg Signal ◽  
Signal Compression ◽  
Type Formula ◽  
Hierarchical Trees ◽  
Electrocardiogram Signal ◽  
Spiht Algorithm ◽  
Electrocardiogram Ecg

In this paper, we propose an electrocardiogram (ECG) signal compression algorithm that is based on wavelet and a new modified set partitioning in hierarchical trees (SPIHT) algorithm. The proposed algorithm contains a preprocessing of the approximation subband before the coding step by mean removing. Three other modifications are also introduced to the SPIHT algorithm. The first one is a new initialization of the two lists of insignificant points (LIP) and insignificant sets (LIS), while the second is concerning the position of inserting new entries of type [Formula: see text] at the LIS, and in the last one, the redundancy in checking type [Formula: see text] entries in the original method was found and avoided. The new proposed coding algorithm is applied to ECG signal compression and the obtained numerical results on the MIT-BIH database show the efficient performances of the proposed SPIHT algorithm over the original method and other existing methods.

scholarly journals SELF-EMBEDDING VIDEO WATERMARKING USING DUAL ORTHOGONAL COMPLEX CONTOURLET TRANSFORM WITH AUTOCORRELATION SYSTEM

2015 ◽  
Vol 3 (4) ◽  
pp. 89-98
Author(s):  
U.R. Padma ◽  
Jayachitra
Keyword(s):  
Communication Channel ◽  
Set Partitioning ◽  
Video Watermarking ◽  
Contourlet Transform ◽  
Huffman Coding ◽  
Data Systems ◽  
Huge Data ◽  
Hierarchical Trees ◽  
Enormous Amount ◽  
Spiht Algorithm

This paper presents a novel non-blind watermarking algorithm using dual orthogonal complex contourlet transform. The dual orthogonal complex contourlet transform is preferred for watermarking because of its ability to capture the directional edges and contours superior to other transforms such as cosine transform, wavelet transform, etc. Digital image and video in their raw form require an enormous amount of storage capacity and the huge data systems also contain a lot of redundant information.Compression also increases the capacity of the communication channel. Image Compression using SPIHT Set Partitioning in Hierarchical Trees algorithm based on Huffman coding technique. SPIHT algorithm is the lossless compression algorithms reduce file size with no loss in image quality and comparing the final results in terms of bit error rate, PSNR and MSE.

BINARY-UNCODED IMAGE AND VIDEO COMPRESSION USING SPIHT-ZTR CODING

2011 ◽  
Vol 11 (03) ◽  
pp. 415-437 ◽  
Author(s):  
WAI CHONG CHIA ◽  
LI WERN CHEW ◽  
LI-MINN ANG ◽  
KAH PHOOI SENG
Keyword(s):  
Video Compression ◽  
Set Partitioning ◽  
Tree Structure ◽  
Video Sequences ◽  
Hierarchical Trees ◽  
Ezw Algorithm ◽  
Spiht Algorithm ◽  
Adaptive Arithmetic Coding ◽  
Parent Node ◽  
Image And Video Compression

When the embedded zerotree wavelet (EZW) algorithm was first introduced by Shapiro, four types of symbols (zerotree (ZTR), isolated zero (IZ), positive (POS), and negative (NEG)) were used to represent the tree structure. An improved version of EZW, the set partitioning in hierarchical trees (SPIHT) algorithm was later proposed by Said and Pearlman. SPIHT removed the ZTR symbol, while keeping the other three symbols in a slightly different form. In the SPIHT algorithm, the coding of the parent node is isolated from the coding of its descendants in the tree structure. Therefore, it is no longer possible to encode the parent and its descendants with a single symbol. When both the parent and its descendants are insignificant (forming a degree-0 zerotree (ZTR)), it cannot be represented using a ZTR symbol. From our observation, the number of degree-0 ZTRs can occur very frequently not only in natural and synthesis images, but also in video sequences. Hence, the ZTR symbol is reintroduced into SPIHT in our proposed SPIHT-ZTR algorithm. In order to achieve this, the order of sending the output bits was modified to accommodate the use of ZTR symbol. Moreover, the significant offspring were also encoded using a slightly different method to further enhance the performance. The SPIHT-ZTR algorithm was evaluated on images and video sequences. From the simulation results, the performance of binary-uncoded SPIHT-ZTR is higher than binary-uncoded SPIHT and close to SPIHT with adaptive arithmetic coding.

scholarly journals Block-Adaptive Lattice Vector Quantization in Image Coding

1970 ◽  
Vol 7 (2) ◽  
pp. 126-134
Author(s):  
Wisarn Patchoo ◽  
Thomas R. Fischer
Keyword(s):  
Vector Quantization ◽  
Image Coding ◽  
Integer Lattice ◽  
Set Partitioning ◽  
Lattice Vector ◽  
Product Code ◽  
Hierarchical Trees ◽  
Spiht Algorithm ◽  
Complexity Constraints ◽  
Better Than

A subband image coding algorithm is described based on lattice-based spherical VQ and lattice-based pyramid VQ. The algorithm partitions a subband (or wavelet) decomposed image into blocks of various sizes, depending on their energy and complexity constraints on the enumeration encoding of lattice codevectors. Each block is lattice vector quantized and encoded using a product code. The algorithm is simple and effective, exploiting energy clustering in a wavelet transformed image. Using the integer lattice, the algorithm provides performance slightly better than the Set-Partitioning Embedded Block (SPECK) algorithm, and is competitive with JPEG2000 and the set partitioning in hierarchical trees (SPIHT) algorithm.

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