Low-memory low-complexity inverse dithering

Dithering an image decreases the pixel bit depth and reduces the storage space required in the image buffer while largely preserving the perceptual quality. In some applications, it is desirable to reconstruct the original image; that is, restore the dithered image to its original bit-depth, for further processing or display. In this paper, we present a new color inverse dithering system designed for low-cost implementation. Our algorithm is based on edge-sensitive adaptive low-pass filtering. In order to prevent excessive blurring from low pass filtering, the system uses edge detection methods so that the filters are applied only to regions of constant color or gray level in the original image. One such method exploits the fact that pixel values are only one level away from each other in a constant color region of a dithered image. Another method exploits a priori knowledge of the dither masks. By limiting the number of possible filters, and by restricting the region of support of the filters to a single image line, tremendous implementation advantages can be gained. Our prototype system uses a set of five filters, including a pair that are asymmetric about the origin specifically for application to object edges. In our implementation, the need for multipliers is eliminated by using bit replication for up-multiplication, and by using lookup tables with relatively small numbers of entries for filtering. We have found that our inverse dithering system can restore to a significant degree a dithered image to its original form. It is especially effective for graphics and synthetic images.