Weighted aggregation and fuzzy-concept-guided signal resemblance and expansion for video format conversion

In this paper, we propose an efficient deinterlacing method for HDTV that preserves image structures, edges, and details. In the human visual system, the eyes are more sensitive to high-frequency information such as edge details than low-frequency information such as image background. Therefore, averaging low-pass filter results is not effective for image enhancement. The proposed method is a weighted filtering approach that generates a half-pixel 9-by-9 edge-based line average window. We also propose pixel-resemblance- and pixel-expansion-based fuzzy weights, which are assigned using a triangular membership function. Compared to conventional format conversion methods, the proposed method outperforms all benchmarks in terms of both objective and subjective qualities.