Fast multiscale directional filter bank-based speckle mitigation in gallstone ultrasound images

Abstract

Speckle noise is a multiplicative type of noise commonly seen in medical and remote sensing images. It gives a granular appearance that degrades the quality of the recorded images. These speckle noise components need to be mitigated before the image is used for further processing and analysis. This paper presents a novel approach for removing granular speckle noise in gray scale images. We used an efficient multiscale image representation scheme named fast multiscale directional filter bank (FMDFB) along with simple threshold methods such as Vishushrink for image processing. It is a perfect reconstruction framework that can be used for a wide range of image processing applications because of its directionality and reduced computational complexity. The FMDFB-based speckle mitigation is appealing over other traditional multiscale approaches such as wavelets and Contourlets. Our experimental results show that the despeckling performance of the proposed method outperforms the wavelet and Contourlet-based despeckling methods.

Design of FIR Filters for Fast Multiscale Directional Filter Banks

“…Figure 2 shows the frequency resolution of contourlet, MDFB and FMDFB. Also, the total number of subband coefficients will be equal to the size of the original image and thereby maintaining the maximally decimated property [7]. As stated in [6], perfect reconstruction is always possible at all scales regardless of the low-pass filters used for decomposition.…”

“…In order to satisfy the criteria, equiripple hL[n] with pass band edge 0.3 Π and stop band edge 0.5 Π are designed [9,10]. Also, the Laplacian pyramid is designed with orthogonal filters i.e., h L [n] = g L [−n] to ensure lossless reconstruction.…”

Analysis and Modeling of Statistical Properties of FMDFB Subband Coefficients

“…Fast multiscale directional filter bank is an image representation scheme that is successfully used in feature extraction and image enhancement (Cheng, Law, & Siu, 2007a), ( Cheng, Law, & Siu, 2007b). In our previous work, an image denoising scheme with FMDFB is proposed that works well for additive Gaussian and multiplicative speckle noise removal compared to other conventional multiscale denoising methods such as wavelet 803 and contourlet based denoising (Leavline, Sutha, & Singh, 2014a). Yet, the statistical nature of the FMDFB subbands has not been analyzed.…”

“…In our previous work, we have introduced a multiscale denoising approach using FMDFB for Gaussian and speckle noise removal (Leavline et al, 2014a;Leavline & Sutha, 2011).…”

Intelligent speckle reducing anisotropic diffusion algorithm for automated 3-D ultrasound images

“…Speckle noise is a granular pattern that is seen commonly in coherent imaging systems, such as ultrasound (US), optical coherence tomography (OCT), and synthetic aperture radar (SAR) imaging [1,2]. In this paper, we focus on multiplicative noise removal problems in the 3-D ultrasound images.…”