A gradient guided deinterlacing algorithm

This paper proposes new intra and inter-deinterlacing algorithm based on the gradient domain image/video processing approach. From the interlaced (field) images, gradient field images are generated and then the gradients of missing lines are estimated to generate gradient images which correspond to progressive frames. The proposed intra-deinterlacing is basically an edge-oriented interpolation, which interpolates the gradients of missing pixels along the optimal spatial orientation. Finding the optimal orientation among all possible ones is formulated as a labeling problem with Markov random field (MRF) framework. For obtaining better results for fast moving video sequences, this method is extended to inter-deinterlacing, which considers the temporal orientations as well as the spatial ones. With the synthesized gradient frame images and the original pixel values of the field images, we then formulate a linear equation that generates the final progressive frame images. Like other gradient domain image processing applications, the integrity of edges is the main advantage of the proposed method.