scholarly journals A New Multi-level Error Diffusion Method Based on Fuzzy Inference

2003 ◽  
Vol 123 (10) ◽  
pp. 1910-1911
Author(s):  
Noriaki Suetake ◽  
Masanori Togashi
Author(s):  
Noriaki Suetake ◽  
◽  
Masanori Togashi ◽  

We propose a new multi-level error diffusion method employing the fuzzy inference, which realizes half toning with high quality. In the proposed method, dissimilar textures around quantization levels, which are the cause of the low image quality and obtained by a conventional method, are decreased by using fuzzy inference. In this paper, we apply the proposed method to various standard digital images. The image quality of the result using the proposed method is higher than those of other methods without noise-add filtering, and it is almost same as them with filtering in 2 or 3 times faster processing.


2020 ◽  
Vol 64 (5) ◽  
pp. 50410-1-50410-9
Author(s):  
Donghui Li ◽  
Takuma Kiyotomo ◽  
Takahiko Horiuchi ◽  
Midori Tanaka ◽  
Kaku Shigeta

Abstract Digital halftoning is a technique for converting a continuous-tone image into a quantized image to reproduce it on a digital printing device. Error diffusion (ED) is an algorithm that has proven to be effective for the halftoning process, and it has been widely applied to digital printing tasks. However, in images reproduced using conventional ED algorithms based on the signal processing theory, the texture of objects is often lost. In this study, we propose a texture-aware ED algorithm for multi-level digital halftoning. First, we generate multiple mapped images with different brightness levels through nonlinear transformation. For each mapped image, we adopt a texture-aware binary error diffusion method to obtain multiple halftone images. Finally, we generate a multi-level halftone image from the multiple halftone images. We test the algorithm on an actual printer, compare the results with those of the current raster image processor software and classical ED algorithms, and observe that our algorithm outputs better results.


2019 ◽  
Vol 58 (20) ◽  
pp. 5547 ◽  
Author(s):  
Gao Yang ◽  
Shuming Jiao ◽  
Jung-Ping Liu ◽  
Ting Lei ◽  
Xiaocong Yuan

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