scholarly journals Development of an advanced method for compressing the dynamic component of a differential-represented frame

2020 ◽  
Vol 68 (3) ◽  
Author(s):  
O. I. Tymochko ◽  
◽  
V. V. Larin ◽  
Yu. I. Shevyakov ◽  
A. Abdalla ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Compression Ratio ◽  
Differential Form ◽  
Block Code ◽  
Low Complexity ◽  
Video Data ◽  
Compact Representation ◽  
Binary Mask ◽  
Subsequent Formation ◽  
Dynamic Component

For a typical low complexity video sequence, the weight of each P-frame in the stream is approximately three times smaller than the I-frame weight. However, taking into account the number of P-frames in the group, they make the main contribution to the total video data amount. Therefore, the possibility of upgrading coding methods for P-frames is considered on preliminary blocks' type identification with the subsequent formation of block code structures. As the correlation coefficient between adjacent frames increases, the compression ratio of the differential-represented frame's binary mask increases. The compression ratio of the differential-represented frame's binary mask varies from 3 to 21 depending on the correlation coefficient between adjacent frames. Estimation of the bit representation's information content of the differential-represented frame's binary mask on the basis of accounting for the nonequilibrium of the bases of the lengths of the binary series does not require an increase in the complexity of the software-hardware implementation. Due to the double-alphabetic power code, the differential-represented frame's binary mask is relative to the single-alphabet code will decrease by 17%. The most preferable method for constructing the compact representation technology of the binary masks of frames represented in a differential form is the approach. This is based on the identification and description of the lengths of one-dimensional binary series. A binary series is a consecutive binary elements sequence with the same value. In this case, sequences of identical binary elements are replaced by their lengths. And since the elements of the binary masks of the frames represented in the differential form take only two possible values 0 or 1, it is suggested to form the lengths of the binary series without indicating their level.

scholarly journals The video processing features research in computer systems and special purpose networks

2020 ◽  
pp. 126-132
Author(s):  
Ю.І. Шевяков ◽  
В.В. Ларін ◽  
є.л. Казаков ◽  
Ахмед Абдалла
Keyword(s):  
Correlation Coefficient ◽  
Compression Ratio ◽  
Video Processing ◽  
Video Sequence ◽  
Block Code ◽  
Low Complexity ◽  
Video Data ◽  
Compact Representation ◽  
Binary Mask ◽  
Subsequent Formation

For a typical low complexity video sequence, the weight of each P-frame in the stream is approximately three times smaller than the I-frame weight. However, taking into account the number of P-frames in the group, they make the main contribution to the total video data amount. Therefore, the possibility of upgrading coding methods for P-frames is considered on preliminary blocks' type identification with the subsequent formation of block code structures. As the correlation coefficient between adjacent frames increases, the compression ratio of the differential-represented frame's binary mask increases. The compression ratio of the differential-represented frame's binary mask varies from 3 to 21 depending on the correlation coefficient between adjacent frames. The most preferable method for constructing the compact representation technology of the binary masks of frames represented in a differential form is the approach. This is based on the identification and description of the lengths of one-dimensional binary series. A binary series is a consecutive binary elements sequence with the same value. In this case, sequences of identical binary elements are replaced by their lengths.

An Effective Spectrum Sensing Method Based on Correlation Coefficient and Energy Detection

2014 ◽  
Vol 1023 ◽  
pp. 210-213
Author(s):  
Fu Lai Liu ◽  
Shou Ming Guo ◽  
Rui Yan Du
Keyword(s):  
Correlation Coefficient ◽  
Spectrum Sensing ◽  
Dynamic Spectrum Access ◽  
Energy Detection ◽  
Low Complexity ◽  
Noise Power ◽  
Decision Threshold ◽  
Test Statistic ◽  
Receiving Antenna ◽  
Influence Of Noise

Spectrum sensing is the key functionality for dynamic spectrum access in cognitive radio networks. Energy detection is one of the most popular spectrum sensing methods due to its low complexity and easy implementation. However, performance of the energy detector is susceptible to uncertainty in noise power. To overcome this problem, this paper proposes an effective spectrum sensing method based on correlation coefficient. The proposed method utilizes a single receiving antenna with a delay device to acquire the original received signal and the delayed signal. Then the correlation coefficient of the two signals is computed and the result is used as the test statistic. Theoretical analysis shows that the decision threshold is unrelated to noise power, thus the proposed approach can effectively overcome the influence of noise power uncertainty. Simulation results testify the effectiveness of the proposed method even in low signal-to-noise (SNR) conditions.

scholarly journals Lossless and Low-Power Image Compressor for Wireless Capsule Endoscopy

VLSI Design ◽  
2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Tareq Hasan Khan ◽  
Khan A. Wahid
Keyword(s):  
Low Power ◽  
Compression Ratio ◽  
Low Complexity ◽  
Cmos Technology ◽  
Silicon Area ◽  
Endoscopic Images ◽  
Prediction Scheme ◽  
Image Pixels ◽  
Image Compressor ◽  
Wireless Capsule

We present a lossless and low-complexity image compression algorithm for endoscopic images. The algorithm consists of a static prediction scheme and a combination of golomb-rice and unary encoding. It does not require any buffer memory and is suitable to work with any commercial low-power image sensors that output image pixels in raster-scan fashion. The proposed lossless algorithm has compression ratio of approximately 73% for endoscopic images. Compared to the existing lossless compression standard such as JPEG-LS, the proposed scheme has better compression ratio, lower computational complexity, and lesser memory requirement. The algorithm is implemented in a 0.18 μm CMOS technology and consumes 0.16 mm × 0.16 mm silicon area and 18 μW of power when working at 2 frames per second.

scholarly journals A Low-Complexity and High-Decoding Performance Scheme for the MIMO-SCMA System

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Wenping Ge ◽  
Haofeng Zhang ◽  
Shiqing Qian ◽  
Lili Ma ◽  
Gecheng Zhang
Keyword(s):  
Error Rate ◽  
Message Passing ◽  
Multiple Input Multiple Output ◽  
High Capacity ◽  
Block Code ◽  
Low Complexity ◽  
Spectrum Efficiency ◽  
Performance Loss ◽  
Message Passing Algorithm ◽  
Input Multiple Output

Sparse code multiple access (SCMA) has been proposed to obtain high capacity and support massive connections. When combined with the multiple-input multiple-output (MIMO) techniques, the spectrum efficiency of the SCMA system can be further improved. However, the detectors of the MIMO-SCMA system have high computational complexity. For the maximum likelihood (ML) detection, though it is optimal decoding algorithm for the MIMO-SCMA system, the detection complexity would grow exponentially with the number of both the antennas and users increase. In this paper, we consider a space-time block code (STBC) based MIMO-SCMA system where SCMA is used for multiuser access. Besides, we propose a low-complexity utilizing joint message passing algorithm (JMPA) detection, which narrowing the range of superimposed constellation points, called joint message passing algorithm based on sphere decoding (S-JMPA). But for the S-JMPA detector, the augment of the amount of access users and antennas leads to the degradation of decoding performance, the STBC is constructed to compensate the performance loss of the S-JMPA detector and ensure good bit error rate (BER) performance. The simulation results show that the proposed method achieves a close error rate performance to ML, JMPA, and a fast convergence rate. Moreover, compared to the ML detector, it also significantly reduces the detection complexity of the algorithms.

scholarly journals Efficient Turbo Inter-Leaver Based MIMO-OFDM System For Low Complexity Outdoor Communication

2019 ◽  
Vol 9 (1) ◽  
pp. 3154-3162
Keyword(s):  
Communication Systems ◽  
Orthogonal Frequency Division Multiplexing ◽  
Mimo System ◽  
Block Code ◽  
Low Complexity ◽  
Turbo Coding ◽  
Maximum Ratio Combining ◽  
High Data ◽  
Coding Scheme ◽  
Multiple Paths

An arrangement of multiple antennas in both the receiver and transmitter called Multiple Input and Multiple Output (MIMO). The Orthogonal Frequency Division Multiplexing (OFDM) is enabled in MIMO system for high data wireless communications. Combination of both MIMO and OFDM Access (OFDMA) is a growing technology in next generation communication systems. In this work, the Bit Error Rate (BER) performance of MIMO-OFDMA is analyzed with Orthogonal Space Time Block Code (OSTBC), Maximum Ratio Combining (MRC) and Turbo coding scheme over flat fading channel are named as MIMO-MRC-OFDMA. OSTBC is a transmit diversity scheme, which is utilized for delivering an efficient transmission with high peak data rates that significantly improves the capacity of communication systems. Successively, the MRC diversity solves transmit and receive diversity from an OSTBC. MRC approach is applied in the receiving end for summing and weighing the received signals from the multiple paths. Besides, turbo coding scheme is utilized for error correction in a given code rate. The proposed system performance is evaluated in light of BER by varying the number of receive and transmit antennas such as 2×2, 2×4, 4×2 and 4×4

scholarly journals Low Complexity Automatic Stationary Wavelet Transform for Elimination of Eye Blinks from EEG

2019 ◽  
Vol 9 (12) ◽  
pp. 352
Author(s):  
Mohammad Shahbakhti ◽  
Maxime Maugeon ◽  
Matin Beiramvand ◽  
Vaidotas Marozas
Keyword(s):  
Wavelet Transform ◽  
Correlation Coefficient ◽  
Signal To Noise Ratio ◽  
Low Complexity ◽  
Stationary Wavelet Transform ◽  
Eeg Signals ◽  
Real Time Processing ◽  
Eye Blink ◽  
Eye Blinks ◽  
Components Analysis

The electroencephalogram signal (EEG) often suffers from various artifacts and noises that have physiological and non-physiological origins. Among these artifacts, eye blink, due to its amplitude is considered to have the most influence on EEG analysis. In this paper, a low complexity approach based on Stationary Wavelet Transform (SWT) and skewness is proposed to remove eye blink artifacts from EEG signals. The proposed method is compared against Automatic Wavelet Independent Components Analysis (AWICA) and Enhanced AWICA. Normalized Root Mean Square Error (NRMSE), Peak Signal-to-Noise Ratio (PSNR), and correlation coefficient ( ρ ) between filtered and pure EEG signals are utilized to quantify artifact removal performance. The proposed approach shows smaller NRMSE, larger PSNR, and larger correlation coefficient values compared to the other methods. Furthermore, the speed of execution of the proposed method is considerably faster than other methods, which makes it more suitable for real-time processing.

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