Design and implementation for deinterlacing using the edge-based correlation adaptive method

Deinterlacing is a method to construct a complete image from an interlaced signal. The interlaced signal format is adopted by the Natural Television System Committee (NTSC) based on eye remanence. In previous work, such as traditional edge line averaging (ELA), it used the intra-interpolation to find the minimum difference value without considering the edge and boundary existence. Consequently, it will cause the interpolation value to be blurred at the edge. A novel algorithm, an edge-based correlation adaptive (ECA) method, is proposed. ECA is based on various edge directions to detect the edge. This new intrafield method has better performance on smoothing the edge and stripe. ECA is improved by using a weighted summation of the ELA component to facilitate the interpolation result. We also interpolate the half-pixel value to increase the accuracy for edge detection. We also mention the architecture and very large scale integration (VLSI) implement results.