Quality evaluation of the halftone by halftoning algorithm-based methods and adaptive method

Digital halftoning algorithm is a operation, converting the captured con-tone images to the corresponding binary images supported by most output devices, which makes the tow kinds of images similar as possible. In order to evaluate the halftoning algorithms and the corresponding halftones, a criterion must be needed. In the literature, MSE (the Mean Square Error), SNR (Signal to Noise Ratio) and WSNR(Weight Signal to Noise Ratio) were often used to evaluate the common con-tone images and the halftones. But these methods do not suit to evaluating the quality of the halftones because of the special properties of the halftones by different halftoning algorithms and limitation of assumption of these methods themselves according to many researches. So a series of halftonig algorithm-based methods are proposed, which adapt to the special properties of halftoning algorithms. All of those methods were not adaptive. In the last part of this paper, an adaptive method was propose to evaluate the halftoning algorithms and the corresponding halftones, which is based on the statistical features of the residual image between the original image and the corresponding halftone on the retinal of human eye.