scholarly journals A Novel VLSI Architecture for SPHIT Encoder

2013 ◽  
Vol 10 (4) ◽  
pp. 1522-1530
Author(s):  
Haritha Motupalle ◽  
Syed Jahangir Badashah
Keyword(s):  
Vlsi Architecture ◽  
Image Transmission ◽  
Set Partitioning ◽  
Compression Scheme ◽  
Storage And Retrieval ◽  
Test Circuit ◽  
Hardware Description ◽  
Image Storage And Retrieval ◽  
Spiht Algorithm ◽  
Bit Stream

In this Paper we propose a highly scalable image compression scheme based on the set partitioning in hierarchical trees (SPIHT) algorithm. Our algorithm called highly scalable SPIHT (HS-SPIHT), supports spatial and SNR scalability and provides a bit stream that can be easily adapted (reordered) to given bandwidth and resolution requirements by a simple transcoder (parser). The HS-SPIHT algorithm adds the spatial scalability feature without sacrificing the SNR embeddedness property as found in the original SPIHT bit stream. HS-SPIHT finds applications in progressive Web browsing, flexible image storage and retrieval, and image transmission over heterogeneous networks. Here we have written the core processor Microblaze is designed in VHDL (VHSIC hardware description language), implemented using XILINX ISE 8.1 Design suite the algorithm is written in system C Language and tested in SPARTAN-3 FPGA kit by interfacing a test circuit with the PC using the RS232 cable. The test results are seen to be satisfactory. The area taken and the speed of the algorithm are also evaluated.

Performance Analysis of Compression Techniques for Chronic Wound Image Transmission Under Smartphone-Enabled Tele-Wound Network

2021 ◽  
pp. 345-364
Author(s):  
Chinmay Chakraborty
Keyword(s):  
Chronic Wounds ◽  
Signal To Noise Ratio ◽  
Image Transmission ◽  
Set Partitioning ◽  
Compression Technique ◽  
Telemedicine System ◽  
Diagnostic Quality ◽  
Segmentation Accuracy ◽  
Fuzzy C Means Clustering ◽  
Bandwidth Savings

The healing status of chronic wounds is important for monitoring the condition of the wounds. This article designs and discusses the implementation of smartphone-enabled compression technique under a tele-wound network (TWN) system. Nowadays, there is a huge demand for memory and bandwidth savings for clinical data processing. Wound images are captured using a smartphone through a metadata application page. Then, they are compressed and sent to the telemedical hub with a set partitioning in hierarchical tree (SPIHT) compression algorithm. The transmitted image can then be reduced, followed by an improvement in the segmentation accuracy and sensitivity. Better wound healing treatment depends on segmentation and classification accuracy. The proposed framework is evaluated in terms of rates (bits per pixel), compression ratio, peak signal to noise ratio, transmission time, mean square error and diagnostic quality under telemedicine framework. A SPIHT compression technique assisted YDbDr-Fuzzy c-means clustering considerably reduces the execution time (105s), is simple to implement, saves memory (18 KB), improves segmentation accuracy (98.39%), and yields better results than the same without using SPIHT. The results favor the possibility of developing a practical smartphone-enabled telemedicine system and show the potential for being implemented in the field of clinical evaluation and the management of chronic wounds in the future.

A fast ELM-based machine compression scheme for underwater image transmission on a low-bandwidth acoustic channel

Sensor Review ◽  
2019 ◽  
Vol 39 (4) ◽  
pp. 542-553
Author(s):  
Shujing Zhang ◽  
Manyu Zhang ◽  
Yujie Cui ◽  
Xingyue Liu ◽  
Bo He ◽  
...  
Keyword(s):  
Image Compression ◽  
Principal Component ◽  
Image Transmission ◽  
Color Images ◽  
Compression Algorithm ◽  
Divide And Conquer ◽  
Perceptual Quality ◽  
Compression Scheme ◽  
Content Type ◽  
Processing Module

Purpose This paper aims to propose a fast machine compression scheme, which can solve the problem of low-bandwidth transmission for underwater images. Design/methodology/approach This fast machine compression scheme mainly consists of three stages. Firstly, raw images are fed into the image pre-processing module, which is specially designed for underwater color images. Secondly, a divide-and-conquer (D&C) image compression framework is developed to divide the problem of image compression into a manageable size. And extreme learning machine (ELM) is introduced to substitute for principal component analysis (PCA), which is a traditional transform-based lossy compression algorithm. The execution time of ELM is very short, thus the authors can compress the images at a much faster speed. Finally, underwater color images can be recovered from the compressed images. Findings Experiment results show that the proposed scheme can not only compress the images at a much faster speed but also maintain the acceptable perceptual quality of reconstructed images. Originality/value This paper proposes a fast machine compression scheme, which combines the traditional PCA compression algorithm with the ELM algorithm. Moreover, a pre-processing module and a D&C image compression framework are specially designed for underwater images.

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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