scholarly journals An Enhanced Run-Length Encoding Compression Method for Telemetry Data

2017 ◽  
Vol 24 (3) ◽  
pp. 551-562 ◽  
Author(s):  
Yanhu Shan ◽  
Yongfeng Ren ◽  
Guoyong Zhen ◽  
Kaiqun Wang
Keyword(s):  
Compression Ratio ◽  
High Capacity ◽  
Acquisition System ◽  
Compression Method ◽  
Telemetry Data ◽  
Vibration Signals ◽  
Run Length ◽  
Compression Performance ◽  
Error Factor ◽  
Method Show

AbstractThe telemetry data are essential in evaluating the performance of aircraft and diagnosing its failures. This work combines the oversampling technology with the run-length encoding compression algorithm with an error factor to further enhance the compression performance of telemetry data in a multichannel acquisition system. Compression of telemetry data is carried out with the use of FPGAs. In the experiments there are used pulse signals and vibration signals. The proposed method is compared with two existing methods. The experimental results indicate that the compression ratio, precision, and distortion degree of the telemetry data are improved significantly compared with those obtained by the existing methods. The implementation and measurement of the proposed telemetry data compression method show its effectiveness when used in a high-precision high-capacity multichannel acquisition system.

Multi-Channel ECG Signals Compression Algorithm Using Simultaneous Orthogonal Matching Pursuit

2012 ◽  
Vol 457-458 ◽  
pp. 1305-1309
Author(s):  
Yong Ting Li ◽  
Xiao Yan Chen ◽  
Yue Wen Liu
Keyword(s):  
Signal Processing ◽  
Compression Ratio ◽  
Matching Pursuit ◽  
Orthogonal Matching Pursuit ◽  
Compression Method ◽  
Petersburg Institute ◽  
Redundant Dictionary ◽  
Compression Performance ◽  
Ecg Signals ◽  
Ecg Compression

Sparse decompression is a new theory for signal processing, having the advantage in that the base (dictionary) used in this theory is over-complete, and can reflect the nature of signa1. So the sparse decompression of signal can get sparse representation, which is very important in data compression. In this paper, a novel ECG compression method for multi-channel ECG signals was introduced based on the Simultaneous Orthogonal Matching Pursuit (S-OMP). The proposed method decomposes multi-channel ECG signals simultaneously into different linear expansions of the same atoms that are selected from a redundant dictionary, which is constructed by Hermite fuctions and Gobar functions in order to the best match the characteristic of the ECG waveform. Compression performance has been tested using a subset of multi-channel ECG records from the St.-Petersburg Institute of Cardiological Technics database, the results demonstrate that much less atoms are selected to present signals and the compression ratio of Multi-channel ECG can achieve better performance in comparison to Simultaneous Matching Pursuit (SMP).

scholarly journals 3D DCT Based Image Compression Method for the Medical Endoscopic Application

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1817
Author(s):  
Jiawen Xue ◽  
Li Yin ◽  
Zehua Lan ◽  
Mingzhu Long ◽  
Guolin Li ◽  
...  
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Signal To Noise Ratio ◽  
Blocking Artifacts ◽  
Compression Method ◽  
High Compression Ratio ◽  
Multiplication Operation ◽  
3D Data ◽  
Wireless Capsule

This paper proposes a novel 3D discrete cosine transform (DCT) based image compression method for medical endoscopic applications. Due to the high correlation among color components of wireless capsule endoscopy (WCE) images, the original 2D Bayer data pattern is reconstructed into a new 3D data pattern, and 3D DCT is adopted to compress the 3D data for high compression ratio and high quality. For the low computational complexity of 3D-DCT, an optimized 4-point DCT butterfly structure without multiplication operation is proposed. Due to the unique characteristics of the 3D data pattern, the quantization and zigzag scan are ameliorated. To further improve the visual quality of decompressed images, a frequency-domain filter is proposed to eliminate the blocking artifacts adaptively. Experiments show that our method attains an average compression ratio (CR) of 22.94:1 with the peak signal to noise ratio (PSNR) of 40.73 dB, which outperforms state-of-the-art methods.

scholarly journals Parameter space dimension reduction of an adaptive interpolator during multidimensional signal differential compression

2019 ◽  
pp. 23-30
Author(s):  
A I Maksimov ◽  
M V Gashnikov
Keyword(s):  
Dimension Reduction ◽  
Parameter Space ◽  
Compression Ratio ◽  
Space Dimension ◽  
Computational Experiments ◽  
Parameter Range ◽  
Compression Method ◽  
Multidimensional Signals ◽  
Multidimensional Signal ◽  
Adaptive Interpolator

We propose a new adaptive multidimensional signal interpolator for differential compression tasks. To increase the efficiency of interpolation, we optimize its parameters space by the minimum absolute interpolation error criterion. To reduce the complexity of interpolation optimization, we reduce the dimension of its parameter range. The correspondence between signal samples in a local neighbourhood is parameterized. Besides, we compare several methods for such parameterization. The developed adaptive interpolator is embedded in the differential compression method. Computational experiments on real multidimensional signals confirm that the use of the proposed interpolator can increase the compression ratio.

Adaptive Speech Compression Based on Discrete Wave Atoms Transform

2016 ◽  
Vol 6 (5) ◽  
pp. 2150
Author(s):  
Bousselmi Souha ◽  
Aloui Nouredine ◽  
Cherif Adnane
Keyword(s):  
Compression Ratio ◽  
Speech Quality ◽  
Huffman Coding ◽  
Current Work ◽  
Speech Compression ◽  
Snr Estimation ◽  
Run Length ◽  
Compression System ◽  
Wave Atoms ◽  
Wavelets Transform

<p>This paper proposes a new adaptive speech compression system based on discrete wave atoms transform. First, the signal is decomposed on wave atoms, then wave atom coefficients are truncated using a new adaptive thresholding which depends on the SNR estimation. The thresholded coefficients are quantized using Max Lloyd scalar quantizer. Besides, they are encoded using zero run length encoding followed by Huffman coding. Numerous simulations are performed to prove the robustness of our approach. The results of current work are compared with wavelet based compression by using objective criteria, namely CR, SNR, PSNR and NRMSE. This study shows that the wave atoms transform is more appropriate than wavelets transform since it offers a higher compression ratio and a better speech quality.</p>

Application of Texture in a Compressed Visual Simulation

2014 ◽  
Vol 644-650 ◽  
pp. 4261-4264
Author(s):  
Wei Zhang ◽  
Chun Hua Zhang ◽  
Jia Yue Ren
Keyword(s):  
Compression Ratio ◽  
Visual Simulation ◽  
Compression Method ◽  
Texture Memory

Texture compression technology is an effective way to improve the capacity of the texture without increasing the texture memory. This paper studies a texture compression method based on mipmap technology, details several texture compression formats, and describes the texture file of several formats generating and corresponding parameters adjustment. Practical results show that the texture compression method based on mipmap technology can not only achieve high texture compression ratio, but also cause no effect on the texture quality.

A New Compression Method for Bayer Color Filter Array Images

2013 ◽  
Vol 321-324 ◽  
pp. 1219-1224
Author(s):  
Bao Tang Shan ◽  
Fa Nian Wang ◽  
Juan Gao
Keyword(s):  
Image Compression ◽  
High Performance ◽  
Lossless Compression ◽  
Color Filter ◽  
Test Results ◽  
Compression Method ◽  
Sampling System ◽  
Multiple Channel ◽  
Compression Performance ◽  
Filter Array

In order to improve the compression performance of Bayer CFA images exposed continuously, a new high performance remainder set near-lossless compression method is presented. Based on channel-separated-filtering, several typical Bayer CFA image compression methods are compared with the proposed remainder set algorithm. It is proved that the remainder set algorithm has not only the better compression performance, i.e., the lower bits per pixel (average about 2.16bpp), but also the better reconstructed CFA image PSNR (average about 52.31dB). Finally, the proposed method is employed in a multiple channel CMOS image sampling system and some test results are given.

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