Weighted Fuzzy Reasoning Scheme for Interlaced to Progressive Conversion

Video deinterlacing can be realized using time-space interpolation filters. To improve video deinterlacing quality with respect to missing pixels on moving diagonal lines, we developed a fuzzy concept that utilizes deinterlacing methods. The proposed algorithm consists of three parts. The first part is fuzzy rule-assisted edge-preserving-based deinterlacing (FED), which has an edge-preserving unit that utilizes fuzzy theory to find the most accurate edge direction and interpolates the missing pixels. Using the introduced gradients in the interpolation, the vertical resolution in the deinterlaced image is subjectively concealed. The second part is weighted fuzzy-reasoning-assisted deinterlacing (WFD), which works in the spatio-temporal domain. In this part, the computed weights are considered and multiplied by the candidate deinterlaced pixels, which successively build approximations of the deinterlaced sequence. The third part of the proposed algorithm is weighted fuzzy switching filtering, which analyzes the suitability of each method on system performance and uses a switching algorithm between FED and WFD. The outcome of image interpolation can be adjusted continuously by varying the setting of the membership function for fuzzy inference. Compared with conventional image interpolation methods, the algorithm presented in this paper provides improved edge quality in the deinterlaced image without the introduction of evident artifacts.