Ultrasound Image Enhancement Using Laplacian Kernel Set

Abstract: Biomedical imaging methods are very vital for health care services. The random noise in the biomedical images may cause critical damage to the patient. The aim of this thesis was to investigate the advanced restoration and enhancement filters, identify their merits and demerits and propose new filters to overcome the drawbacks of the existing filters. For this purpose kernel set based filters were applied to normal ultrasound image. The performance parameters such as signal to noise ratio (SNR), peak signal to noise ratio (PSNR), root mean square error (RMSE), mean absolute error (MAE), and Pearson correlation coefficient (PCC) have been estimated and compared.

Keywords: Ultrasound, Kernel set, Laplacian, SNR, PSNR.