SQbSN: JPEG2000 scalar quantizer implemented by means a statistical normalization

In this work we present an algorithm for quantizing wavelet coefficients taking in to account to be used by any image compression system that use wavelet transformation, we particularly implemented it in JPEG2000. In the literature is well-know that any wavelet-base compression encoder considers three stages: 1) Conversion of pixel into the frequency domain in order to obtain coefficients; 2) Scalar Quantization; and 3) Coding of the wavelet quantized coefficients. By one hand is important to highlight that just Scalar Quantization stage is responsible for degraded or maintaining precision of a certain coefficient, thus if the accuracy of inverse quantized coefficient is reduced we can consider a lossy reconstruction otherwise when inverse quantized coefficient is perfectly reconstructed we consider a lossless reconstruction with Scalar Quantization equal to one. By the other hand, we modify the state-of-The-Art and classical JPEG2000 dead-zone scalar quantization modifying the process with a Statistical Normalization or better known as Z-Scores. We can define a Z-score as a expression in terms of standard deviations distributed along their mean. Thus, Z-scores can be defined as distribution with μ = 0 and σ² = 0, in this way visual redundancies of the image are incremented, which gives as a result a lower compression rate.