Inverse Halftoning Method Based on Multi-scale and Multi-level Information Adaptive Fusion Network

LI Mei; KONG Weixuan

doi:10.19554/j.cnki.1001-3563.2025.11.021

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Packaging Engineering ›› 2025, Vol. 46 ›› Issue (11) : 195-204. DOI: 10.19554/j.cnki.1001-3563.2025.11.021

Automatic and Intelligent Technology

Inverse Halftoning Method Based on Multi-scale and Multi-level Information Adaptive Fusion Network

LI Mei, KONG Weixuan

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Abstract

Inverse halftoning method is a key technique to restore inverse halftone images, which has been used for digital file management and high precision image recognition. The existing inverse halftone methods have some problems such as missing image content, fuzzy reproduction of image details. To relieve the shortcomings of existing methods, the work aims to propose an inverse halftoning method based on multi-scale and multi-level information adaptive fusion. Firstly, the effective multi-scale adaptive deep convolutional network was proposed to extract the multi-scale information. Then, the detailed information of the halftone image were extracted effectively by the combination of dense residual blocks and attention mechanism. Finally, the multi-information adaptive fusion deep convolutional network was constructed to obtain high quality inverse halftone images by fusing the content information and detailed information recovered from different stages effectively. Extensive experiments were conducted on three public datasets, such as Set14, Urban100 and Microsoft COCO₃, and compared with the 5 state-of-the-art methods. The experimental results show that in terms of objective evaluation, the mean peak signal-to-noise ratio increased by 0.05-5.51 dB, and the mean structural similarity increased by 0-0.1. In terms of subjective evaluation, the inverse halftone image obtained by the proposed method was more similar to the original image visually, the halftone noise was removed more thoroughly and the image details were better restored. Moreover, the average runtime running on a GPU of the proposed network was 0.13 s for an image with the size of 256 pixel×256 pixel, which meant that the proposed network could meet the requirements of practical applications. The proposed multi-scale and multi-level information adaptive fusion model can achieve the inverse halftone image of better quality.

Key words

inverse halftoning method / multi-scale adaptive deep network / multi-information adaptive fusion deep network / halftone image

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LI Mei, KONG Weixuan. Inverse Halftoning Method Based on Multi-scale and Multi-level Information Adaptive Fusion Network[J]. Packaging Engineering. 2025, 46(11): 195-204 https://doi.org/10.19554/j.cnki.1001-3563.2025.11.021

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