Speckle noise, which arises in coherent illumination of diffusing target, is a principal factor limiting performance of a laser bar code scanner and its miniaturization. Speckle noise cannot be eliminated using tradition signal processing methods, like Fourier domain filtering, averaging of several signals, or denoising by wavelet shrinkage.
The author will present a denoising method using a nonlinear filtering in a "quasi" wavelet space. First, a signal is transformed by means of an integral transformation, which resembles Continuous Wavelet Transform (CWT). However, a family of wavelets for different scales is generated not by dilation, like it would have been in the CWT, but in another, systematic way. Proposed transformation, we call it QCWT (Quasi CWT), seems to be invertible, and each wavelet fulfills the wavelet admissibility condition. The advantage of such approach is that "wavelets" match closely elements of bar code signals, which allows for better performance. Local maxima of the transformed signal are used for the denoising process. Additionally statistical properties inferred from signal are used to reduce the required computations.
The proposed method allows for decoding bar codes with signal-to-noise ratio lower by 10 dB, and is compared to other advanced methods used in laser scanners.