A visually adaptive quantization method of DCT-based images based on Human Visual System(HVS) is proposed. This approach uses the spatial masking in HVS characteristics to obtain higher compression ratio with relatively small degradation in the image quality. HVS is nonsensitive to an edge area, so a high complexity area is quantized coarsely in contrast to fine quantization of the low complexity area. The complexity of an area is estimated by the variance of DCT coefficients of the image. Experimental results demonstrate the performance of the proposed method and the resulting images show little difference from the original image in the subjective perception.