Servizio Comunitario di Informazione in materia di Ricerca e Sviluppo - CORDIS

Multichannel nonlinear filters for colour image restoration and enhancement of highly corrupted colour images

A multichannel nonlinear vector median based edge enhancing filter has been developed for colour image processing. The first filtering stage consists of three subfilters; whereas, the final output is obtained through comparing the subfilter outputs and the vector median output. The resulting multichannel filter is shown to enhance degraded edges in colour images. Nonlinear multivariate image filtering techniques are proposed to handle colour images corrupted by noise. Three reduced orderings are defined by selecting three different central locations. Considering noise attenuation, edge preservation and detail retention, multivariate filters are designed by combining R-ordering schemes. Locally adaptive versions of these techniques are also developed. Another locally adaptive multichannel filter based on the concept of trimmed mean filtering is developed for the purpose of colour image enhancement. The output of the filter is the mean of some subset selected from the input samples in the current window. These subsets are selected using the distance information from the marginal median and the centre sample. Suitable choices for the size of these subsets control the noise attenuation and detail preservation of the proposed filter. The next scheme developed for u image restoration decomposes the filtering process into two phases: directional estimation and magnitude estimation. The two phases can be computed simultaneously .The directional estimate is obtained by the basic directional filter; while, the magnitude estimate can be obtained by a number of scalar or vector filtering. Vector median (VM) and VM alternating with the mean filter have been used in a non-adaptive and adaptive schemes, respectively, yielding good results for colour image restoration. The final technique developed for colour image restoration concerns images which have been highly corrupted with impulse noise and for which conventional processing fails.

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Tampere University of Technology
Hermiankatu 12 C
33720 Tampere
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