Image denoising in acoustic field microscopy

TL;DR

This paper introduces a denoising method for acoustic microscopy images using block matching filters on low amplitude signals, improving image clarity over traditional filtering techniques.

Contribution

The study proposes a novel block matching filter approach for denoising SAM images, outperforming conventional filters in low amplitude signal conditions.

Findings

Block matching filter effectively denoises low amplitude SAM images.

Compared to Gaussian, median, Wiener, and total variation filters, the proposed method shows improved image quality.

Results demonstrate enhanced detail preservation in acoustic microscopy images.

Abstract

Scanning acoustic microscopy (SAM) has been employed since microscopic images are widely used for biomedical or materials research. Acoustic imaging is an important and well-established method used in nondestructive testing (NDT), bio-medical imaging, and structural health monitoring.The imaging is frequently carried out with signals of low amplitude, which might result in leading that are noisy and lacking in details of image information. In this work, we attempted to analyze SAM images acquired from low amplitude signals and employed a block matching filter over time domain signals to obtain a denoised image. We have compared the images with conventional filters applied over time domain signals, such as the gaussian filter, median filter, wiener filter, and total variation filter. The noted outcomes are shown in this article.