Beltrami-Regularized Denoising Filter Based on Tree Seed Optimization Algorithm: An Ultrasound Image Application

The dominant degrading factor of quality in ultrasound images is mainly due to the occurrence of speckle noise that in turn leads to false ameliorative decisions, restricts auto diagnosis and telemedicine practices. In medical image analysis speckle reduction is contemplated to be the pre-processing task that sustains decisive information and exclude speckle noise. Meta-heuristics optimization algorithm were used now a days for speckle reduction problems. Our contribution in this paper analyses the use of optimization technique in determining the best noise removing filter coefficients that removes the speckle content contributively. The proposed method comprises the use of Finite Impulse Response filter receiving the filter coefficients from Tree Seed optimization algorithm. Evaluation of noise removal with standard metrics such as Peak Signal to Noise Ratio, Correlation coefficient and Structural Similarity Index shows that the proposed method gives optimal speckle reduction score when compared with conventional filters and its superiority in despeckling medical ultrasound images. Assessment of the proposed methodology with advanced evaluation metrics ensures the ability of it in terms of preserving edges and textural features.