An Effective SALS Image Denoising Method based on 2-D Discrete Wavelet Decomposition

Abstract

This paper describes an effective small angle light scattering (SALS) image denoising method based on 2-D discrete wavelet decomposition. The phenomenon of small angle light scattering has been applied to giving information about transparent structures on morphology. The potential of using SALS to probe morphological changes induced by flow in polymer melts is investigated. Well-defined flow of polymer melts histories in a visual slit die are shown to result in SALS patterns that are characteristic for the morphology involved. The current study utilizes a 2-D discrete wavelet to delete noise from the original SALS image and estimate the variation trend of maximum intensity area of the scattered light. To compare the SALS denoising result, four commonly used wavelets, named haar wavelet, db2 wavelet, Coi4 and Sym5 wavelet are taken into account. It can also be observed that db2 wavelet obtain the best denoising result in the four wavelts.