Compared to the traditional threshold stack filters

mirrored threshold stack filters have been empowered not only with lowpass filtering characteristics but with bandpass and highpass characteristics as well

but their positive Boolean functions length leads to an increasing restriction during calculation. In order to solve the above problems

this paper proposes a mirrored adaptive weight (MAW) algorithm

which calculates cost vector based on adaptive neighbor weight error criterion (ANWMAE). After cost vector stacking is restricted and its astringency is estimated

the optimal positive Boolean function of stack filters is confirmed to construct adaptive weight mirrored threshold stack filters (AWMSF). In order to testify the filtering capability

AWMSF was simulated

the results show that it can suppress noise and protect the details of image effectively

the number of iterations is reduced and the computing complication is decreased rapidly too.