A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital halftoning
Elements of the Theory of Computation
Elements of the Theory of Computation
Inverse halftoning via MAP estimation
IEEE Transactions on Image Processing
Inverse error-diffusion using classified vector quantization
IEEE Transactions on Image Processing
Inverse halftoning using wavelets
IEEE Transactions on Image Processing
A fast, high-quality inverse halftoning algorithm for error diffused halftones
IEEE Transactions on Image Processing
Hybrid LMS-MMSE inverse halftoning technique
IEEE Transactions on Image Processing
Look-up table (LUT) method for inverse halftoning
IEEE Transactions on Image Processing
Tree-structured method for LUT inverse halftoning and for image halftoning
IEEE Transactions on Image Processing
Inverse halftoning algorithm using edge-based lookup table approach
IEEE Transactions on Image Processing
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The recently published edge- and lookup table-based inverse halftoning (ELIH) algorithm has shown its quality and superiority when compared with the previous lookup table-based IH algorithm. This paper presents a new finite state machine model (FSMM)-based search method to speed up the existing ELIH algorithm significantly while preserving the same image quality as in the ELIH algorithm. From the observation that the sliding window for the ELIH algorithm moves from left to right one position; there are therefore one output column and one input column which are introduced at each step and thus a simple finite state machine can track the transitions from the current window movement to the next. This is faster than a full search in the lookup table. Under thirty typical testing images adopted from Mese's website, experimental results demonstrated that the proposed FSMM-based ELIH algorithm has an improvement in execution time of 20% to 80%, with a typical improvement of 50%, when compared to the ELIH algorithm.