SPECKLE NOISE REDUCTION USING HYBRID TMAV BASED FUZZY FILTER

Abstract

The multiplicative nature of speckle noise present in imaging modalities like echocardiography complicates the despeckling procedure as it would be necessary to remove noise with the edges well preserved. A novel speckle reduction technique based on integration of moving average filter using fuzzy triangulation membership function (TMAV) with moving average center with wiener filter is proposed and analyzed in this paper. Fuzzy TMAV filter is experimented for reduction of speckle noise in homomorphic domain. Denoising features of this filter are fine tuned by sequentially embedding it with wiener filter. This hybrid TMAV filters result in the enhancement of edges with higher amount of noise reduction. The performance of proposed filter is compared with ten state-of-art denoising techniques. Figure of merit (FOM), structural similarity (SSIM) index along with traditional parameters are superior for hybrid fuzzy filters in comparison to methods like probability patch based (PPB), Non-local means (NLM), and posterior sampling based Bayesian estimation (PSBE) based filters.