Title :
A family of nonlinear filters with data dependent coefficients
Author :
Economou, G. ; Fotopoulos, S. ; Vemis, M.
Author_Institution :
Electron. Lab., Patras Univ., Greece
fDate :
1/1/1995 12:00:00 AM
Abstract :
A new family of data dependent nonlinear filters (DDNL) is presented. Coefficients are computed locally and the absolute distance between signal samples is used to determine a rank order dependent weighting function. The new filters have very good performance regarding noise suppression and impulse rejection and at the same time provide better edge preservation than the averager and other linear smoothers
Keywords :
filtering theory; image processing; image sampling; noise; nonlinear filters; averager; data dependent coefficients; edge preservation; impulse rejection; linear smoothers; noise suppression; nonlinear filters; performance; rank order dependent weighting function; signal samples; Face; Finite impulse response filter; Gaussian noise; Information filtering; Information filters; Nonlinear filters; Signal processing; Signal processing algorithms; Smoothing methods; Working environment noise;
Journal_Title :
Signal Processing, IEEE Transactions on
