RTL DESIGN OF EFFICIENT MODIFIED RUN-LENGTH ENCODING ARCHITECTURES USING VERILOG HDL
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This document describes the design of efficient modified run-length encoding architectures for data compression and decompression using Verilog HDL. The modified run-length encoding algorithm uses lossy compression to improve compression ratio over standard run-length encoding. Verilog modules for the compression and decompression algorithms were designed, simulated, and synthesized using Xilinx ISE 13.1. Simulation results demonstrated that the compression architecture achieved higher compression than standard run-length encoding and decompression correctly reconstructed the original data.
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International Journal of Electronics and Communication Engineering and Technology (IJECET)
Volume 8, Issue 1, January - February 2017, pp. 52–57, Article ID: IJECET_08_01_006
Available online at
http://www.iaeme.com/IJECET/issues.asp?JType=IJECET&VType=8&IType=1
ISSN Print: 0976-6464 and ISSN Online: 0976-6472
© IAEME Publication
RTL DESIGN OF EFFICIENT MODIFIED RUN-
LENGTH ENCODING ARCHITECTURES USING
VERILOG HDL
Swetha Annangi
Assistant Professor, ECE Department,
Guru Nanak Institute of Technology, Hyderabad, Telangana, India
ABSTRACT
Compression is an efficient technique to reduce the memory size and to improve the speed. In
ECG signal compression, modified run-length encoding plays a significant role to compress the
digitized ECG signals. The main objective of this paper is to realize an efficient architecture for
modified run-length encoding compression and decompression algorithms. The proposed
architectures designed in verilog HDL. And the designed verilog HDL modules are simulated and
synthesized using Xilinx ISE 13.1 for RTL design.
Key words: Modified Run-Length Encoding; Compression; Decompression; Verilog HDL; RTL
Design.
Cite this Article: Swetha Annangi, RTL Design of Efficient Modified Run-Length Encoding
Architectures Using Verilog HDL, International Journal of Electronics and Communication
Engineering and Technology, 8(1), 2017, pp. 52–57.
http://www.iaeme.com/IJECET/issues.asp?JType=IJECET&VType=8&IType=1
1. INTRODUCTION
In modern Bio-medical signal processing, the storage, processing and transmission of large quantities of
digitized ECG signals for reproductive purpose is required. Data compression is needed to reduce the space
required to store and transmit digitized ECG signals [1]. In discrete wavelet transform based ECG signal
compression alorithm, firstly the ECG signals are decomposed by using forward discrete wavelet
transformation. Secondly the thresholding will be done for the decomposed signals. Next modified run-
length encoding and decoding is done to compress and decompress the digitisized signals. Lastly the
reconstruction will be done by using inverse discrete wavelet transformation.
Compression can be done in two ways- lossless compression and lossy compression. Lossless
compression is a class of data compression algorithm that allows the original data to be perfectly
reconstructed from the compressed data. The original data and the data after compression and
decompression are exactly the same because no part of the data is lost in the process [2]. Lossy
compression discards the partial data to represent the content. This is used to reduce data size for storage,
handling and transmitting content. In most cases a lossy method can produce a much smaller compared file
than any lossless method, while still meeting the requirements of the applications. Lossy methods are most
often used for compressing sound, images or videos.](https://image.slidesharecdn.com/ijecet0801006-170310101729/85/RTL-DESIGN-OF-EFFICIENT-MODIFIED-RUN-LENGTH-ENCODING-ARCHITECTURES-USING-VERILOG-HDL-1-320.jpg)
![RTL Design of Efficient Modified Run-Length Encoding Architectures Using Verilog HDL
http://www.iaeme.com/IJECET/index.asp 57 editor@iaeme.com
5. CONCLUSION
In this paper, Lossy data compression is used to design efficient modified run-length encoding
compression and decompression architectures using verilog HDL. And the designed modules are simulated
and synthesized using Xilinx ISE 13.1. The given input sequence is encoded using compression algorithm.
And decompression algorithm is applied to the compressed data to get the original sequence. Lossy data
compression is used to compress the data. By using these architectures, the efficient compression rate is
achieved.
REFERENCES
[1] Mohammed Abo-Zahhad (2011). ECG Signal Compression Using Discrete Wavelet Transform, Discrete
Wavelet Transforms - Theory and Applications, Dr. Juuso T. Olkkonen (Ed.), ISBN: 978-953-307-185-
5, InTech, Available from: http://www.intechopen.com/books/discrete-wavelet-transforms-theory-
andapplications/ecg-signal-compression-using-discrete-wavelet-transform.
[2] S. Joseph, N. Srikanth, J. E. N. Abhilash, “A Novel Approach of Modified Run-Length Encoding
Scheme for High Speed Data Communication Application,” International journal of Science and
Research, ISSN: 2319-7064, Vol. 2, Issue 12, December 2013.
[3] S. Sarika, S. Srilali, “Improved Run Length Encoding Scheme for Efficient Compression Data Rate,”
International Journal of Engineering Research and Applications, ISSN: 2248-9622, Vol. 3, Issue 6, Nov-
Dec 2013.
[4] Muhammad Bilal Akhtar, Dr. Qamar-ul-Islam , “Open Source Algorithm for Storage Area and
Temporally Optimized Run Length Coding for Image Compression Technology Used in Biomedical
Imaging,” International Conference on Open Source Systems and Technologies, 2012.
[5] Varsha Bansall, Pratishtha Gupta, Suhail Tomar, “The Implementation of Run Length Encoding for
RGB Image Compression,” International Journal of Advanced Research in Computer Engineering &
Technology (IJARCET), ISSN: 2278 – 1323, Volume 3 Issue 12, December 2014.
[6] Scitt Hauck, William D. Wilson, “Runlength Compression Techniques for FPGA Configurations,” IEEE
Symposium on FPGAs for Custom Computing Machines, 1999.
[7] Md. Ajmal Sadiq, T. Naga Raju and Kumar. Keshamoni, Modeling and Simulation of Test Data
Compression Using Verilog, International Journal of Electronics and Communication Engineering &
Technology, 4 (5), 2013, pp. 143–141.
[8] Bangaru Kalpana, Amrut Anilrao Purohit and R. Venkata Siva Reddy, Area Optimization of SPI
Module Using Verilog HDL, International Journal of Electronics and Communication Engineering &
Technology(IJECET), 7 (3), 2016, pp. 38–45.](https://image.slidesharecdn.com/ijecet0801006-170310101729/85/RTL-DESIGN-OF-EFFICIENT-MODIFIED-RUN-LENGTH-ENCODING-ARCHITECTURES-USING-VERILOG-HDL-6-320.jpg)
RTL DESIGN OF EFFICIENT MODIFIED RUN-LENGTH ENCODING ARCHITECTURES USING VERILOG HDL
- 1. http://www.iaeme.com/IJECET/index.asp 52 [email protected] International Journal of Electronics and Communication Engineering and Technology (IJECET) Volume 8, Issue 1, January - February 2017, pp. 52–57, Article ID: IJECET_08_01_006 Available online at http://www.iaeme.com/IJECET/issues.asp?JType=IJECET&VType=8&IType=1 ISSN Print: 0976-6464 and ISSN Online: 0976-6472 © IAEME Publication RTL DESIGN OF EFFICIENT MODIFIED RUN- LENGTH ENCODING ARCHITECTURES USING VERILOG HDL Swetha Annangi Assistant Professor, ECE Department, Guru Nanak Institute of Technology, Hyderabad, Telangana, India ABSTRACT Compression is an efficient technique to reduce the memory size and to improve the speed. In ECG signal compression, modified run-length encoding plays a significant role to compress the digitized ECG signals. The main objective of this paper is to realize an efficient architecture for modified run-length encoding compression and decompression algorithms. The proposed architectures designed in verilog HDL. And the designed verilog HDL modules are simulated and synthesized using Xilinx ISE 13.1 for RTL design. Key words: Modified Run-Length Encoding; Compression; Decompression; Verilog HDL; RTL Design. Cite this Article: Swetha Annangi, RTL Design of Efficient Modified Run-Length Encoding Architectures Using Verilog HDL, International Journal of Electronics and Communication Engineering and Technology, 8(1), 2017, pp. 52–57. http://www.iaeme.com/IJECET/issues.asp?JType=IJECET&VType=8&IType=1 1. INTRODUCTION In modern Bio-medical signal processing, the storage, processing and transmission of large quantities of digitized ECG signals for reproductive purpose is required. Data compression is needed to reduce the space required to store and transmit digitized ECG signals [1]. In discrete wavelet transform based ECG signal compression alorithm, firstly the ECG signals are decomposed by using forward discrete wavelet transformation. Secondly the thresholding will be done for the decomposed signals. Next modified run- length encoding and decoding is done to compress and decompress the digitisized signals. Lastly the reconstruction will be done by using inverse discrete wavelet transformation. Compression can be done in two ways- lossless compression and lossy compression. Lossless compression is a class of data compression algorithm that allows the original data to be perfectly reconstructed from the compressed data. The original data and the data after compression and decompression are exactly the same because no part of the data is lost in the process [2]. Lossy compression discards the partial data to represent the content. This is used to reduce data size for storage, handling and transmitting content. In most cases a lossy method can produce a much smaller compared file than any lossless method, while still meeting the requirements of the applications. Lossy methods are most often used for compressing sound, images or videos.
- 2. RTL Design of Efficient Modified Run http://www.iaeme.com/IJECET/index.asp In this paper, lossy data compression is used to design efficient modified run compression and decompression architectures using verilog HDL. And the designed modules are simulated and synthesized using Xilinx ISE 13.1. 2. RUN LENGTH ENCODING Run length encoding algorithm uses lossless data compression technique. In the run le runs (identical data) of data are stored as a single value and count, rather than as the original data. For example, if the input sequence is 44, 44, 44, 44, 45, 45, 27, 27, 26, 26 then the output sequence will be (44, 4), (45, 2), (27, 2), (26, 2). From the above example it is clear that, the compression ratio is better for the longer runs of data. 3. EFFICIENT MODIFIED R 3.1. Compression The efficient modified run length encoding compression algorithm uses lossy compre this lossy compression, the compression ratio can be improved, which causes to improve the system performance as well. In this technique, first input data is printed at the output. If the next input data is equal to or 1 bit greater than or 1 bit less than the previous data, then this data is considered in the run and count is incremented. If the modified run length encoding algorithm is applied to the same example mentioned above, 44, 44, 44, 44, 45, 45, 27, 27, 26, 26 then instead of output sequence will be (44, 6), (27,4). From the example it is known that the compression ratio is improved when compared to run length encoding. The flow chart of compression algorithm is given in figure1. RTL Design of Efficient Modified Run-Length Encoding Architectures Using Verilog HDL http://www.iaeme.com/IJECET/index.asp 53 In this paper, lossy data compression is used to design efficient modified run compression and decompression architectures using verilog HDL. And the designed modules are simulated and synthesized using Xilinx ISE 13.1. RUN LENGTH ENCODING Run length encoding algorithm uses lossless data compression technique. In the run le runs (identical data) of data are stored as a single value and count, rather than as the original data. For example, if the input sequence is 44, 44, 44, 44, 45, 45, 27, 27, 26, 26 then the output sequence will be (44, ), (26, 2). From the above example it is clear that, the compression ratio is better for the EFFICIENT MODIFIED RUN LENGTH ENCODING The efficient modified run length encoding compression algorithm uses lossy compre this lossy compression, the compression ratio can be improved, which causes to improve the system performance as well. In this technique, first input data is printed at the output. If the next input data is han or 1 bit less than the previous data, then this data is considered in the run and count is incremented. If the modified run length encoding algorithm is applied to the same example mentioned above, 44, 44, 44, 44, 45, 45, 27, 27, 26, 26 then instead of (44, 4), (45, 2), (27, 2), (26, 2), the output sequence will be (44, 6), (27,4). From the example it is known that the compression ratio is improved when compared to run length encoding. The flow chart of compression algorithm is given in figure1. Figure 1 Encoding Architectures Using Verilog HDL [email protected] In this paper, lossy data compression is used to design efficient modified run-length encoding compression and decompression architectures using verilog HDL. And the designed modules are simulated Run length encoding algorithm uses lossless data compression technique. In the run length encoding the runs (identical data) of data are stored as a single value and count, rather than as the original data. For example, if the input sequence is 44, 44, 44, 44, 45, 45, 27, 27, 26, 26 then the output sequence will be (44, ), (26, 2). From the above example it is clear that, the compression ratio is better for the The efficient modified run length encoding compression algorithm uses lossy compression technique. With this lossy compression, the compression ratio can be improved, which causes to improve the system performance as well. In this technique, first input data is printed at the output. If the next input data is han or 1 bit less than the previous data, then this data is considered in the run and count is incremented. If the modified run length encoding algorithm is applied to the same example (44, 4), (45, 2), (27, 2), (26, 2), the output sequence will be (44, 6), (27,4). From the example it is known that the compression ratio is
- 3. http://www.iaeme.com/IJECET/index.asp The algorithm for modified run-length encoding compression algorithm is described below. • Read first data from the input sequence. • Print first data. • Print count=1. • Read next data. • If next data=first data or first data+1 or first data • Print count=count+1. • Go to step 4. • Print next data. • Go to step 3. Figure 2 shows the architecture of modified run 3.2. Decompression The flow chart of decompression algorithm is Swetha Annangi http://www.iaeme.com/IJECET/index.asp 54 length encoding compression algorithm is described below. Read first data from the input sequence. If next data=first data or first data+1 or first data-1 then go to step 6. Otherwise go to step 8. Figure 2 shows the architecture of modified run-length encoding compression algorithm. Figure 2 The flow chart of decompression algorithm is given in figure 3. Figure 3 [email protected] length encoding compression algorithm is described below. 6. Otherwise go to step 8. length encoding compression algorithm.
- 4. RTL Design of Efficient Modified Run http://www.iaeme.com/IJECET/index.asp The algorithm for modified run-length encoding compression algorithm is described below. • Read input data and count. • Print input data. • Count=count-1. • If count=1 then go to step 1. Otherwise go to step 2. Figure 4 shows the architecture of modified run 4. RESULTS The modified run-length encoding compression and decompression architectures are designed using Verilog HDL. The designed modules are simulated and synthesized using shows the RTL schematic of decompression algorithm. The output waveform of modified run RTL Design of Efficient Modified Run-Length Encoding Architectures Using Verilog HDL http://www.iaeme.com/IJECET/index.asp 55 length encoding compression algorithm is described below. If count=1 then go to step 1. Otherwise go to step 2. itecture of modified run-length encoding compression algorithm. Figure 4 length encoding compression and decompression architectures are designed using Verilog HDL. The designed modules are simulated and synthesized using Xilinx ISE 13.1. and figure 8 shows the RTL schematic of decompression algorithm. The output waveform of modified run-length encoding compression module is shown in figure 5. Figure 5 Encoding Architectures Using Verilog HDL [email protected] length encoding compression algorithm is described below. length encoding compression algorithm. length encoding compression and decompression architectures are designed using Xilinx ISE 13.1. and figure 8 length encoding compression module is shown in figure 5.
- 5. http://www.iaeme.com/IJECET/index.asp The output waveform of modified run Figure 7 shows the RTL schematic of modified run Figure 8 shows the RTL schematic of modified run Swetha Annangi http://www.iaeme.com/IJECET/index.asp 56 The output waveform of modified run-length encoding decompression module is shown in figure 6. Figure 6 Figure 7 shows the RTL schematic of modified run-length encoding compression architecture. Figure 7 Figure 8 shows the RTL schematic of modified run-length encoding decompression architecture. Figure 8 [email protected] module is shown in figure 6. length encoding compression architecture. length encoding decompression architecture.
- 6. RTL Design of Efficient Modified Run-Length Encoding Architectures Using Verilog HDL http://www.iaeme.com/IJECET/index.asp 57 [email protected] 5. CONCLUSION In this paper, Lossy data compression is used to design efficient modified run-length encoding compression and decompression architectures using verilog HDL. And the designed modules are simulated and synthesized using Xilinx ISE 13.1. The given input sequence is encoded using compression algorithm. And decompression algorithm is applied to the compressed data to get the original sequence. Lossy data compression is used to compress the data. By using these architectures, the efficient compression rate is achieved. REFERENCES [1] Mohammed Abo-Zahhad (2011). ECG Signal Compression Using Discrete Wavelet Transform, Discrete Wavelet Transforms - Theory and Applications, Dr. Juuso T. Olkkonen (Ed.), ISBN: 978-953-307-185- 5, InTech, Available from: http://www.intechopen.com/books/discrete-wavelet-transforms-theory- andapplications/ecg-signal-compression-using-discrete-wavelet-transform. [2] S. Joseph, N. Srikanth, J. E. N. Abhilash, “A Novel Approach of Modified Run-Length Encoding Scheme for High Speed Data Communication Application,” International journal of Science and Research, ISSN: 2319-7064, Vol. 2, Issue 12, December 2013. [3] S. Sarika, S. Srilali, “Improved Run Length Encoding Scheme for Efficient Compression Data Rate,” International Journal of Engineering Research and Applications, ISSN: 2248-9622, Vol. 3, Issue 6, Nov- Dec 2013. [4] Muhammad Bilal Akhtar, Dr. Qamar-ul-Islam , “Open Source Algorithm for Storage Area and Temporally Optimized Run Length Coding for Image Compression Technology Used in Biomedical Imaging,” International Conference on Open Source Systems and Technologies, 2012. [5] Varsha Bansall, Pratishtha Gupta, Suhail Tomar, “The Implementation of Run Length Encoding for RGB Image Compression,” International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), ISSN: 2278 – 1323, Volume 3 Issue 12, December 2014. [6] Scitt Hauck, William D. Wilson, “Runlength Compression Techniques for FPGA Configurations,” IEEE Symposium on FPGAs for Custom Computing Machines, 1999. [7] Md. Ajmal Sadiq, T. Naga Raju and Kumar. Keshamoni, Modeling and Simulation of Test Data Compression Using Verilog, International Journal of Electronics and Communication Engineering & Technology, 4 (5), 2013, pp. 143–141. [8] Bangaru Kalpana, Amrut Anilrao Purohit and R. Venkata Siva Reddy, Area Optimization of SPI Module Using Verilog HDL, International Journal of Electronics and Communication Engineering & Technology(IJECET), 7 (3), 2016, pp. 38–45.