level quantization
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Information ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 143
Author(s):  
Hyung-Hwa Ko

Binary MQ arithmetic coding is widely used as a basic entropy coder in multimedia coding system. MQ coder esteems high in compression efficiency to be used in JBIG2 and JPEG2000. The importance of arithmetic coding is increasing after it is adopted as a unique entropy coder in HEVC standard. In the binary MQ coder, arithmetic approximation without multiplication is used in the process of recursive subdivision of range interval. Because of the MPS/LPS exchange activity that happens in the MQ coder, the output byte tends to increase. This paper proposes an enhanced binary MQ arithmetic coder to make use of look-up table (LUT) for (A × Qe) using quantization skill to improve the coding efficiency. Multi-level quantization using 2-level, 4-level and 8-level look-up tables is proposed in this paper. Experimental results applying to binary documents show about 3% improvement for basic context-free binary arithmetic coding. In the case of JBIG2 bi-level image compression standard, compression efficiency improved about 0.9%. In addition, in the case of lossless JPEG2000 compression, compressed byte decreases 1.5% using 8-level LUT. For the lossy JPEG2000 coding, this figure is a little lower, about 0.3% improvement of PSNR at the same rate.



2021 ◽  
pp. 31-36
Author(s):  
Georgy I. Volovich

There are given the results of influence the level quantization to the accuracy of measured AC voltage by digital voltmeter. It is shown the influence of sampling frequency and the type of digital filter to effective digit capacity of conversion in case of synchronous and asynchronous sampling. There is obtained an estimate of error by representing the quantization error by centered noise with a uniform distribution. There are presented the results of modeling a digital voltmeter.





2020 ◽  
Vol 6 (11) ◽  
pp. 2000439
Author(s):  
Stefan Petzold ◽  
Eszter Piros ◽  
Robert Eilhardt ◽  
Alexander Zintler ◽  
Tobias Vogel ◽  
...  


Author(s):  
Oleksiy Bahatskji ◽  
Valentyn Bahatskji

At the V.M. Glushkov Institute of Cybernetics the “Yakist-E1” – electric power quality measuring device, was developed. The device uses new method and structure of a quality determination, and is based on calculating the deviations from the nominal values of voltage and frequency values. The methodical error of level quantization for a 10-bit ADC is ± 0.1%. To achieve an approximation error of ± 0.1%, it is necessary to measure the voltage near the amplitude value after 170 μs. The channel for voltage measuring in the device consists of a voltage transformer, a high-precision resistive divider that scales and biases the input voltage, a reference voltage source (VREF) and an ADC, which built into the microcontroller. The device “Yakist-E1” uses an 8-bit microcontroller type C8051F320, which has a 10-bit ADC with an input signal range from 0 to 2.5 V. The output voltage of the VREF from the chip to the controller chip can vary from 2.38 V to 2.5 V. In addition, different transformer sensors may have different transfer characteristics, which may be non-linear. Therefore, to indicate the values of the measured voltage on the alphanumeric indicator, a piecewise linear approximation of the results of measuring the ADC is used. The transfer and temperature characteristics of the voltage transformer were measured for forward and reverse passages, and, according to the results, was discovered that the temperature error is very small and practically does not affect the accuracy of the sensor and the sensor has hysteresis, the calculated errors do not exceed ± 1%. All this errors were corrected. To determine the deviation of the amplitude value from the nominal value, only 8 low-order bits of the ADC are used. This trick grants that ADC result can be processed by a single command of the microcontroller, which increases processing speed of the channel.



2020 ◽  
Vol 11 (1) ◽  
Author(s):  
M. Lyatti ◽  
M. A. Wolff ◽  
I. Gundareva ◽  
M. Kruth ◽  
S. Ferrari ◽  
...  


2019 ◽  
Vol 78 ◽  
pp. 398-408 ◽  
Author(s):  
Haibing Yin ◽  
Xiaofeng Huang ◽  
Dong Li ◽  
Yu Lu ◽  
Yang Zhou


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