Community Research and Development Information Service - CORDIS

Signal-adaptive filters for noise removal in still images and image sequences

Noise corruption of images is a frequently encountered problem in many image processing tasks. The need emerges for implementing smoothing techniques that are able to treat different kinds of noise. The main objectives of image filtering algorithms are: the smoothness of noise in homogeneous regions; the preservation of edges; the removal of impulses of constant as well as of random value. A class of filters that fulfils these requirements is the so called signal-adaptive filters. The morphological signal-adaptive median filter is a paradigm of this class. It performs well on many kinds of noise and does not require the a priori knowledge of a noise-free image, but only of certain noise characteristics easily estimated. It adapts its behaviour based on a local signal to noise (SNR) measurement achieving thus edge preservation and noise smoothing in homogeneous regions. Through the use of an anisotropic local window adaptation procedure, by employing binary morphological erosions and dilations with predefined structuring elements, the largest possible window size is determined at each pixel location thus allowing better noise smoothing in flat regions or edge borders without edge blurring. In the filter capabilities, satisfactory smoothness of impulsive noise is included due to its enhanced impulse detection mechanism able to further detect randomly-valued impulses. The filter proves to perform very well in severe noise corruption cases.


Ioannis PITAS, (Researcher)
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