Digital halftoning algorithm using visual-optimized binary patterns

Digital halftoning is a gray level rendition in devices that have limited gray representation capabilities. The major evaluation points of digital halftoning methods are the image quality and the processing speed. A new halftoning method using a non-thresholding process is proposed, which simply constructs a halftoning database to achieve real time halftoning as well as optimal image quality. The proposed algorithm is constructed by two major parts. The first part is to generate well-distributed binary patterns for every gray level. A contrast sensitivity function (CSF) is used as a filter to distribute void and cluster regions and as a criterion of iteration. The second part is to index the halftoning database to image pixel value. The halftoning database consists of the well-distributed binary patterns. By the proposed algorithm, halftoned images can be obtained faster than the other algorithms and produce similar image quality to those of the max energy mask