A Novel Method for Despeckling of Ultrasound Images Using Cellular Automata-Based Despeckling Filter

Ultrasound images have an inherent property termed as speckle noise that is the outcome of interference between incident and reflected ultrasound waves which reduce image resolution and contrast and could lead to improper diagnosis of any disease. In different approaches for reducing the speckle noise, there exists a class of filters that convert multiplicative noise into additive noise by using algorithmic functions. The current study proposes a cellular automata-based despeckling filter (CABDF) that implements a local spatial filtering framework for the restoration of the noisy image. In the proposed CABDF filter, a dual transition function has been designed which emphasizes the calculation of nearby weighted separation whose loads originate from the CABDF filtered image, including spatial separation, extend inconsistency, and statistical dispersion. The proposed filter found efficient both in terms of filtering and restoration of the original structure of the ultrasound images.

Automated summary

Ultrasound images are often affected by speckle noise, which reduces image quality and can lead to misdiagnosis. A cellular automata-based despeckling filter has been proposed to address this issue, showing efficiency in both filtering and restoring the original structure of ultrasound images.