Abstract
Background: The paper proposes a new method for improving the quality of ultrasound medical images using a two stage wavelet based denoising approach. The first stage utilizes an adaptive wavelet shrinkage function with a novel interscale measure based variance estimate and a new subband adaptive threshold for reducing the speckle present in ultrasound images.
Methods: The performance of the first stage is further improved in the second by employing an error measure estimate. Thus the proposed denoising approach is optimized in the mean square error sense and results in improved noise removal as well as in the edge preservation of the reconstructed image. It also improves the visual quality of the ultrasound images. Next, quantitative evaluation is also done with performance metrics like Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Structural Similarity Index Measure (SSIM), Equivalent Number of Looks (ENL) and Edge preservation Index (EPI).
Results: The performance of the proposed approach is measured and compared with the existing approaches and found to be better in improving the quality of ultrasound images.
Keywords: Ultrasound images, speckle, adaptive filter, undecimated, wavelet, edge preservation.
Graphical Abstract
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