• Journal of Broadcast Engineering
• /
• v.12 no.2
• /
• pp.185-192
• /
• 2007

The interpolation is used in many image processing applications such as image enhancement, de-interlacing/scan-rate conversion, wavelet transforms based on the lifting scheme, and so on. Among these, de-interlacing and scan-rate conversion are proposed for the digital TV applications. The de-interlacing algorithm can be classified into two categories. The first one uses only one field, called intra-field de-interlacing, and the other uses multiple field, called inter-field de-interlacing. In this paper, an efficient de-interlacing algorithm using spatial domain information is proposed far the interpolation of interlaced images. By efficiently estimating the directional correlations, improved interpolation accuracy has been achieved. In addition, the proposed method is simply structured and is easy to implement. Extensive simulations conducted for various images and video sequences have shown the efficacy of the proposed method with significant improvement over the previous intra-field do-interlacing methods in terms of the objective image quality as well as the subjective image quality.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.4C
• /
• pp.217-225
• /
• 2011

In this paper, we propose an adaptive de-interlacing algorithm that is based on the degree of local complexity. The conventional intra field de-interlacing algorithms show the different performance according to the ways which find the edge direction. Furthermore, FDD (Fine Directional De-interlacing) algorithm has the better performance than other algorithms but the computational complexity of FDD algorithm is too high. In order to alleviate these problems, the proposed algorithm selects the most efficient de-interacing algorithm among LA (Line Average), MELA (Modified Edge-based Line Average), and LCID (Low-Complexity Interpolation Method for De-interlacing) algorithms which have low complexity and good performance. The proposed algorithm is trained by the DoLC (Degree of Local Complexity) for selection of the algorithms mentioned above. Simulation results show that the proposed algorithm not only has the low complexity but also performs better objective and subjective image quality performances compared with the conventional intra-field methods.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.3
• /
• pp.20-29
• /
• 2008

In this paper, we propose a do-interlacing algorithm using integral projection-based motion estimation considering Region Of Interest(ROI). The proposed motion estimation method finds the motion of the given ROI accurately with low computational cost. In order to incorporate the motion estimation in do-interlacing, an entire image is first segmented into multiple ROIs according to the temporally predicted block-wise motion types and spatial positions. Then, motion vectors of respective ROIs are obtained by the integral projection method. In this paper, totally five ROIs, one for the global motion and four for the local motions, are made, and therefore, five motion vectors are produced for each field. By using the estimated motion vectors, motion compensation is performed for increasing the vortical resolution of the converted frames. Finally, do-interlaced frames are obtained by effectively combining the results of motion compensation and stable intra-field do-interlacing according to the reliability of motion compensation. Experimental results show that the proposed algorithm provides better image quality than existing algorithms in both subjective and objective measures.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.4C
• /
• pp.371-379
• /
• 2009

In this paper, we proposed new de-interlacing algorithm for video data using intensity gradient filter and median filter with texture detection in the image block. We first introduce the texture detection. According to texture detection, the current region is determined into smooth region or texture region. In case that the smooth region interpolated by median filter. In addition, in case of the texture region, we calculate missing pixel value using intensity gradient filter. Therefore, we analyze the local region feature using the texture detection and classify each missing pixel into two categories. And then, based on the classification result, a different de-interlacing algorithm is activated in order to obtain the best performance. Experimental results show that the proposed algorithm performs well with a variety of moving sequences compared with conventional intra-field method in the literature.