Impulse noise removal on an embedded, low memory SIMD processor

Vector median filters efficiently reduce noise while preserving image details. However, their high computational complexity for color images makes them impractical for real-time systems. We propose new computationally efficient filtering algorithms, called index mapping filters (IMF). These filtering algorithms are accelerated by implementing them on a massively data parallel processor array. In addition to greater computational efficiency, these algorithms result in robust noise reduction of corrupted color images. Analyses of mean square error, signal-to-noise-ratio, and visual comparison metrics indicate that IMF are competitive with the vector median filter (VMF) in their ability to cor…