Quantization Noise of Multilevel Discrete Wavelet Transform Filters in Image Processing
Nikolay Ivanovich Chervyakov, Pavel Alekseyevich Lyakhov, Nikolay Nikolaevich Nagornov · Optoelectronics Instrumentation and Data Processing · 2018
The effect of the quantization noise of the coefficients of discrete wavelet transform (DWT) filters on the image processing result is analyzed. A multilevel DWT method is proposed for determining the effective bit-width of DWT filter coefficients at which quantization noise has little effect on the image processing result. The dependence of the peak signal-to-noise ratio (PSNR) in DWT of images on the wavelet used, the effective bit-width of the coefficients, and the number of processing levels is revealed. Formulas are derived for determining the minimum bit-width of the coefficients that provide high quality of the processed image (PSNR ≥ 40 dB) depending on the wavelet used and the number of processing levels. Experimental modeling of a multilevel DWT image confirmed the results obtained. In the proposed method, all data are represented in fixed-point format, making possible its hardwareefficient implementation on modern devices (FPGA, ASIC, etc.).