A new Speckle Noise Reduction Technique to Suppress Speckle in Ultrasound Images

Medical images like ultrasound images are generally corrupted by speckle noise during their acquisition and transmission. The impact of speckle noise reduces the diagnostic value of the medical image modality. Thus, a speckle noise reduction technique is necessary for the suppression of noise and to retain the fine details from the corrupted image. In this article, a new speckle noise reduction technique has been suggested that uses the concept of absolute difference and mean. A kernel size of 5x5 has been used in the proposed filter and experimented using a standard Lena image, 50 ultrasound nerve tumour images and 25 B-mode ultrasound images as test images. These grayscale images used as test images are induced with speckle noise of variance ranging from 0.01 to 0.09. The performance of the proposed filter is compared with Hybrid Modified Median Filter (HMMF), Adaptive Median Filter (AMF) and Non-local Mean and Cellular Automata Filter (NMCA) reported in the literature and measured in terms of performance measures like Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Signal to Noise Ratio (SNR). The result analysis shows the average PSNR as 31.65, MSE as 46.65 and SNR as 70.34 with noise variance 0.01, the average PSNR as 28.10, MSE as 103.72 and SNR as 66.79 with noise variance 0.05 and the average PSNR as 26.23, MSE as 344 Chithra. K and Santhanam. T 159.33 and SNR as 64.92 with noise variance 0.09 using proposed filter for 50 ultrasound nerve images. The average PSNR as 35.49, MSE as 18.55 and SNR as 78.27 with noise variance 0.01, the average PSNR as 30.51, MSE as 58.80 and SNR as 73.30 with noise variance 0.05 and the average PSNR as 28.37, MSE as 96.34 and SNR as 71.16 for 25 ultrasound B-mode images with noise variance 0.09 of proposed filter.