Wonki Kim
ABSTRACT
This paper presents a novel intra deinterlacing algorithm (NID) based on content adaptive interpolation. The NID consists of three steps: pre-processing, content classification, and content adaptive interpolation. There are also three main interpolation methods in our proposed NID, i.e. modified edge-based line averaging (M-ELA), gradient directed interpolation (GDI), and window matching method (WMM). Each proposed method shows different performances according to spatial local features. Therefore, we analyze the local region feature using the gradient detection and classify each missing pixel into four categories. And then, based on the classification result, a different de-interlacing algorithm is activated in order to obtain the best performance. Experimental results demonstrate that the NID method performs better than previous techniques.
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Cross Ref
- T. Doyle, "Interlaced to sequential conversion for EDTV applications," in proc. 2nd Int. Workshop Signal Processing of HDTV, pp. 412--430, Feb. 1998.Google Scholar
- Tao Chen, Hong Ren Wu, and Zheng Hua Yu, "Efficient Deinterlacing algorithm using edge-based line average interpolation," Optical Engineering, Vol. 39, No. 8, pp. 2101--2105, Aug. 2000.Google ScholarCross Ref
- Hoon Yoo and Jechang Jeong, "Direction-oriented interpolation and its application to de-interlacing," IEEE Trans. Consumer Electronics, vol. 48, Issue 4, pp. 954--962, Nov. 2002. Google ScholarDigital Library
Index Terms
- An efficient intra deinterlacing algorithm with gradient detection and window matching
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