Near-eye display should be miniaturized under the premise of high resolution and high refresh rate， traditional video compression schemes can not meet the demand. The relationship between critical frequency of human eye and eccentricity is quantified， and a viewpoint just noticeable difference model for matching criteria of bit-plane motion estimation is proposed. Search range of the motion estimation is optimized into two parts： time dimension and gray scale dimension. Combined with the human visual system and probability statistical analysis， supplementary matching blocks are added to replace the residual data. A video compression scheme based on bit-plane motion estimation is developed for digitally driven near-eye displays， a controller is designed with field programmable gate array as the core and a system is built for verification. The experimental results show that the compression effect on the lower five bit-planes is the most balanced， the compression ratio is 1.385， and the data transmission volume is constant， which is beneficial to hardware design. The peak signal to noise ratio is 37.658 dB， and the structural similarity is 0.975. There is no obvious difference between the restored image and the original image， which is in line with the intuitive perception of the human eye.