Abstract
In this paper, a spatial domain image deinterlacing method is presented. The goal of this method is to achieve high-quality vertically upsampled images while spending reasonable computational time. We propose directional edge detection approach to recognize edge directions with their own orientations. Assumed and designed number of classified orientations is 11 and each direction has 2 samples. All 22 pixels are categorized into 5 areas, according to the distance from the center pixel. The weighted average approach is applied to restore the missing pixel in a certain window. The employed weights are evaluated by similarity assessment technique. Simulation results show that the proposed method is able to outperform conventional methods in terms of objective (PSNR, SSIM, and consumed time) and subjective metrics.
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