000) divided by the number of bins (101). In other words, the noise amplitude is uniformly distributed between ±LSB/2. If we increase the quantizer resolution, we’ll get an even more uniform amplitude distribution. This
At this point, it is important to clarify that the quantization noise discussed thus far is not statistically independent in nature but rather depends completely on the input signal. Historically, quantization noise has been modeled as a uniform random variable—an approach due in large to the fac...
D. Gibson, "Explicit additive noise models for uniform and nonuni- form MMSE quantization," Signal Processing, vol. 7, pp. 407-414, 1984.K. Sayood and J. D. Gibson, "Explicit additive noise models for uniform and nonuniform MMSE quantization," Signal Processing, vol. 7, pp. 407-414,...
A new technique to reduce the effect of quantization noise in PCM speech coding is proposed. The procedure consists of usingdither noiseto ensure that the quantization errors can be modeled as additive signal-independent noise, and then reducing this noise through the use of a noise reduction sys...
positive definite function. In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering climate data. The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis....
image codingimage reconstructionimage resolutionnoisequantisation (signalDCT quantization noiseDCT-based compressed imagesThe problem of recovering a high-resolution... SC Park,MG Kang,CA Segall,... - Image Processing International Conference on 被引量: 100发表: 2002年 The coding complexity of diffusion...
Randomly dithered quantization and sigma–delta noise shaping for finite frames The main objective of this paper is controlling the mean-square reconstruction error induced by applying randomly dithered quantization, a stochastic round... BG Bodmann,SP Lipshitz - 《Applied & Computational Harmonic Analys...
In the absence of channel noise, variable-length quantizers perform better than fixed-rate LloydMax quantizers for any source with a non-uniform density function. However, channel errors can lead to a loss of synchronization resulting in a propagation of error. To avoid having variable rate, ...
By using (5.11) to (5.15), the output signal-to-noise ratio of a uniform quantizer is as follows: (5.16)SNRo=Pσe2=3σg2V222R=3α222R Equation (5.16) indicates that the SNRo increases exponentially, as the number of bits per sample R is increased. Expressing the SNRo in dB gives...
If we define the difference between the input x and the output Q(x) to be the quantization noise, we can show that the variance of the quantization noise in this situation is Δ2/12. If the distribution of the source output is other than uniform, we can optimize the value of Δ for...