Halftone image resampling by interpolation and error-diffusion
Proceedings of the 2nd international conference on Ubiquitous information management and communication
Speed up of the edge-based inverse halftoning algorithm using a finite state machine model approach
Computers & Mathematics with Applications
Sharing a verifiable secret image using two shadows
Pattern Recognition
Iterated conditional modes for inverse dithering
Signal Processing
Self-verifying visual secret sharing using error diffusion and interpolation techniques
IEEE Transactions on Information Forensics and Security - Special issue on electronic voting
Adaptive energy diffusion for blind inverse halftoning
PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
A new inverse halftoning method using reversible data hiding for halftone images
EURASIP Journal on Advances in Signal Processing
Improved inverse halftoning using vector and texture-lookup table-based learning approach
Expert Systems with Applications: An International Journal
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The inverse halftoning algorithm is used to reconstruct a gray image from an input halftone image. Based on the recently published lookup table (LUT) technique, this paper presents a novel edge-based LUT method for inverse halftoning which improves the quality of the reconstructed gray image. The proposed method first uses the LUT-based inverse halftoning method as a preprocessing step to transform the given halftone image to a base gray image, and then the edges are extracted and classified from the base gray image. According to these classified edges, a novel edge-based LUT is built up to reconstruct the gray image. Based on a set of 30 real training images with both low- and high-frequency contents, experimental results demonstrated that the proposed method achieves a better image quality when compared to the currently published two methods, by Chang et al. and Mes$80e and Vaidyanathan.