A Selective Deinterlacing Based on the Local Feature of Image 


Vol. 29,  No. 1, pp. 140-148, Jan.  2004


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  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)?? method that interpolates long edge very well is used. The linear filter?? 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.

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  Cite this article

[IEEE Style]

D. Woo, I. Eom, Y. Kim, "A Selective Deinterlacing Based on the Local Feature of Image," The Journal of Korean Institute of Communications and Information Sciences, vol. 29, no. 1, pp. 140-148, 2004. DOI: .

[ACM Style]

Dong-Hun Woo, Il-Kyu Eom, and Yoo-Shin Kim. 2004. A Selective Deinterlacing Based on the Local Feature of Image. The Journal of Korean Institute of Communications and Information Sciences, 29, 1, (2004), 140-148. DOI: .

[KICS Style]

Dong-Hun Woo, Il-Kyu Eom, Yoo-Shin Kim, "A Selective Deinterlacing Based on the Local Feature of Image," The Journal of Korean Institute of Communications and Information Sciences, vol. 29, no. 1, pp. 140-148, 1. 2004.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880