LMS 적응 필터링 알고리즘과 에지맵을 이용한 역하프토닝 = Inverse halftoning Using LMS Adaptive Filtering Algorithm and Edge map

다국어 초록 (Multilingual Abstract)

Digital Halftoning convert a continuous-tone images to a binary images. There are many good methods for digital halftoning: ordered dither, error diffusion and more recently direct binary search(DBS). Inverse halftoning addresses the problem of recovering a continuous image from a halftoned binary image.
Simple low pass filtering can remove the high frequency noise but it also removes the edge information. Thus the edge information should be separated from the halftoning noise. As a result, the edge of result image is blurring. The 512×512 continuous tone Lenna image is halftoned by using clustered-dot ordered dithering, dispersed-dot ordered dithering, error diffusion method.
This paper present that we obtain continuous-tone-image which using LMS adaptive filtering algorithm. This image discover the optimal filter weights. To reduce noise without blurring the edges of reconstructed image use edge map.
Simulation results show that proposed method gives a higher PSNR and better subjective quality than conventional methods. As a result, the edge information of reconstructed image reduce blurring.

목차 (Table of Contents)

• 1. 서론
• 2. 디지털 하프토닝 방법
• 2.1 순차적 하프토닝
• 2.2 오차 확산 하프토닝
• 3. 제안된 역하프토닝 방법
• 3.1 LMS 적응필터링 알고리즘
• 3.2 에지맵의 구성
• 4. 실험 및 고찰
• 5. 결론