Displaying natural images on an 8-bit computer monitor requires a substantial reduction of physically distinct colors. Simple minimum mean squared error quantization with 8 levels of red and green and 4 levels of blue yields poor image quality. A powerful means to improve the subjective quality of a quantized image is error diffusion. Error diffusion works by shaping the spectrum of the display error. Considering an image in raster ordering, this is done by adding a weighted sum of previous quantization errors to the current pixel before quantization. These weights form an error diffusion filter. We propose a method to find visually optimized error diffusion filters for monochrome and color image display applications. The design is based on the low-pass characteristic of the contrast sensitivity of the human visual system. The filter is chosen so that a cascade of the quantization system and the observer's visual modulation transfer function yields a whitened error spectrum. The resulting images contain mostly high-frequency components of the display error, which are less noticeable to the viewer. This corresponds well with previously published results about the visibility of halftoning patterns. An informal comparison with other error diffusion algorithms shows less artificial contouring and increased image quality.