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A Selective Deinterlacing Based on the Local Feature of Image  

Woo, Dong-Hun (부산대학교 전자공학과 지능정보처리 연구실)
Eom, Il-Kyu (밀양대학교 정보통신공학과)
Kim, Yoo-Shin (부산대학교 컴퓨터 및 정보통신연구소)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.29, no.1C, 2004 , pp. 140-148 More about this Journal
Abstract
Natural images can be classified into edge or flat region. Edges have also various shapes such as long edge, texture and so on. Because the conventional deinterlacing methods commonly use one specific algorithm, they are faced with the difficulty that does not adapt various shapes of images. In this paper, a selective deinterlacing method based on the characteristics of local region of image is proposed. An input image is classified into three regions; flat region, complex edge, long edge. And then for each region, the proper method is assigned according to the characteristic of the local feature. For long edge region, the modified $NEDI(New Edge Directed Interpolation)^{[1]}$ method that interpolates long edge very well is used. The linear $filter^{[2]}$ that enhances high frequency components is used for complex edge, and the bilinear interpolation method is applied to flat region. The proposed method shows improved performance in PSNR and subjective evaluation compared with previous algorithms.
Keywords
deinterlacing; selective; local feature;
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