An improved error diffusion algorithm based on visual difference

Abstract

Based on the human vision system(HVS), this paper introduces an error diffusion algorithm that produces higher visual quality results while preserving fine texture details and tone consistency present in the original images. We calculate the visual difference between the original and halftone images based on the HVS model. Then by compensating original images for visual difference, reconstructed continuous-tone images that respect the human vision characteristics are obtained. Besides, we use the adaptive median filter to remove noises and preserve sharpness in the reconstructed images. Finally, Floyd-Steinberg E-D using threshold modulation is adopted to get the halftoning results. Multiple experiments show that our method outperforms the existing state-of-art halftoning algorithms and presents visually pleasing results with both fine texture details and clear lines especially in the weak texture and dark tone regions. Meanwhile, our method is much faster due to its simple processing procedure. Combined good visual properties with fast speed, our method can be applicable in most real-world applications.