Standard median filtered bit-plane image segmentation using modified Level Sets

Noise gets added into images during acquisition and transmission. A fundamental problem of image processing is to effectively remove noise from an image while keeping its features intact. Fortunately, two noise models can adequately represent most of the noises added to images: additive Gaussian noise and impulse noise. Impulse noise is characterized by replacing a portion of an image's pixel values with random values, leaving the remainder unchanged. Such noise added due to transmission errors. The most noticeable and least acceptable pixels in the noisy image are those whose intensities are much different from their neighbors. Median filter is a robust method to remove the impulsive noise from an image. In this work we propose two Bit plane architectures to implement the Median filters and perform segmentation of such images was done using modified Level Set method which showed a fast convergence and accurate segmentation of the region.