Abstract: In order to solve the problem of filter hardware and reservation details of the image,this paper proposes a multi-objective evolutionary approach for image filter at function-level.Firstly,the multi-objective optimization model for image filter to minimize the number of large noise pixels and mean absolute error is constructed,and then,gene expression is used as the representation of the image filter,and a two-step off-line search method is to evolve a near-optimal image filter.Finally,the best-evolved gene expression is translated to VHDL and the VHDL is load onto programmable logic device for implementing the image filter.In experiments,three different types of noise are loaded on various images for filter training.The evolved filter by our approach compares various filters,in terms of peak signal to noise ratio(PSNR),mean squared error(MSE) and the effect of filtering.The experimental results illustrated that the proposed multi-objective evolutionary filter is superior to previous filters.