Improved inverse halftoning using vector and texture-lookup table-based learning approach

  • Authors:

  • Yong-Huai Huang;Kuo-Liang Chung;Bi-Ru Dai

  • Affiliations:

  • Institute of Computer and Communication Engineering and Department of Electronic Engineering, Jinwen University of Science and Technology, No. 99, AnChung Rd., Xindian Dist., New Taipei City 23154 ...;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei 10672, Taiwan, ROC;Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, No. 43, Section 4, Keelung Road, Taipei 10672, Taiwan, ROC

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2011

Quantified Score

Hi-index 12.05

Visualization

Abstract

Lookup table-based inverse halftoning (LiH) is a popular approach to reconstruct the gray image from an input halftone image. In this paper, two improved LiH algorithms are presented. We first present a vector- and lookup table-based (VLUT-based) IH algorithm, called the VLIH algorithm, to improve the image quality of the previous LiH algorithm. Different from the previous LiH algorithm which only utilizes the gray value of each pixel to build up the LUT, our proposed VLIH algorithm considers both the gray value of each pixel and its eight neighboring pixels to build up the VLUT. Combining the proposed VLUT and the DCT-based learning scheme, an efficient texture-based VLUT (TVLUT) is built up and it constitutes the kernel of the second proposed IH algorithm called the TVLIH algorithm. Under thirty training images, with satisfactory execution-time requirement, experimental results demonstrate the quality advantage of our proposed VLIH and TVLIH algorithms when compared to the previously published three LiH algorithms.