Abstract
A novel de-interlacing algorithm based on motion objects is presented in this paper. In this algorithm, natural motion objects, not contrived blocks, are considered as the processing cells, which are accurately detected by a new scheme, and whose matching objects are quickly searched by the immune clonal selection algorithm. This novel algorithm integrates many other de-interlacing methods, so it is more adaptive to various complex video sequences. Moreover, it can perform the motion compensation for objects with the translation, rotation as well as the scaling transform. The experimental results illustrate that compared with the block matching method with full search, the proposed algorithm greatly improve the efficiency and performance. © Springer-Verlag 2004.
Cite
CITATION STYLE
Gu, J., Gao, X., & Li, J. (2004). De-interlacing algorithm based on motion objects. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3212, 381–388. https://doi.org/10.1007/978-3-540-30126-4_47
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