Depth Invariant Real-time Fixed/Random Valued Impulse Noise Removal Algorithm for Back-end of Ultrasonography Systems

Ultrasound images often get distorted by impulse noise during data acquisition and processing in the Back-end of the system, which overlay the finer details of the scanned body parts. Generally, a portable low-cost USG system doesn't have an impulse noise-cleaning module which hinders detections of smaller details in the images. A Depth Invariant Impulse Noise Removal (DIINoR) algorithm for real-time impulse noise removal from the corrupt USG image is proposed in this paper. In this decision-based algorithm, the corrupt pixel is first detected depending on the homogeneity of the processing window and is restored with the median of the window or previous pixel value. Testing of the DIINoR algorithm on different USG images establishes that the denoised images have superior quantitative performance compared to those of existing schemes which proves its suitability for the real-time fixed and random valued impulse noise cleaning in the Back-end of the portable USG system.