• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.241-248
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• 2007

In predictive image coding, a LS (Least Squares)-based adaptive predictor is an efficient method to improve image edge predictions. This paper proposes a hybrid interpolation with weighted edge detector. A hybrid approach of switching between bilinear interpolation and EDI (Edge-Directed Interpolation) is proposed in order to reduce the overall computational complexity The objective and subjective quality is also similar to the bilinear interpolation and EDI. Experimental results demonstrate that this hybrid interpolation method that utilizes a weighted edge detector can achieve reduction in complexity with minimal degradation in the interpolation results.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.111-119
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• 2009

This paper presents an adaptive image interpolation algorithm using local characteristics. An input image is classified into edge region and flat low frequency region. And then, the edge region is further partitioned into directive edge region and high frequency texture region. A bilinear interpolation is applied to flat low frequency region, cubic convolution is applied to texture region, and new edge directed interpolation to directive edge region, respectively. Simulation results show that the proposed algorithm outperforms the existing interpolation methods in terms of visual quality as well as PSNR.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1066-1072
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• 2009

This paper proposes a method to reduce the complexity and improve the performance for gentle-slope edges which is the disadvantage of deinterlacing algorithm using the new edge-directed interpolation. To improve the performance for gentle-slope edges, the proposed algorithm increases the number of neighboring reference pixels. To reduce the artifacts and the computational complexity, the proposed algorithm adaptively determines the number of neighboring reference pixels. With computer simulations for a variety of images, it shows that the proposed algorithm provides improved performance in PSNR and subjective evaluation compared with the existing algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8C
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• pp.696-702
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• 2007

This paper proposes a regional feature preserving adaptive interpolation algorithm for natural images. The algorithm can be used in resolution enhancement, arbitrary rotation and other applications of still images. The basic idea is to first scan the sample image to initialize a 2D array which records the edge direction of all four-pixel squares, and then use the array to adapt the interpolation at a higher resolution based on the edge structures. A hybrid approach of switching between bilinear and triangulation-based interpolation is proposed to reduce the overall computational complexity. The experiments demonstrate our adaptive interpolation and show higher PSNR results of about max 2 dB than other traditional interpolation algorithms.

• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.619-630
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• 2013

In this paper, we propose an edge directed color demosaicing algorithm considering color channel correlation. The proposed method consists of local region classification step and edge directional interpolation step. In the first step, each region of a given Bayer image is classified as normal edge, pattern edge, and flat regions by using intra channel and inter channel gradients. Especially, two criteria and verification process for the normal edge and pattern edge classification are used to reduce edge direction estimation error, respectively. In the second step, edge directional interpolation process is performed according to characteristics of the classified regions. For horizontal and vertical directional interpolations, missing color components are obtained from interpolation equations based on intra channel and inter channel correlations in order to improve the performance of the directional interpolations. The simulation results show that the proposed algorithm outperforms conventional approaches in both objective and subjective terms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1C
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• pp.140-148
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• 2004

Natural images can be classified into edge or flat region. Edges have also various shapes such as long edge, texture and so on. Because the conventional deinterlacing methods commonly use one specific algorithm, they are faced with the difficulty that does not adapt various shapes of images. In this paper, a selective deinterlacing method based on the characteristics of local region of image is proposed. An input image is classified into three regions; flat region, complex edge, long edge. And then for each region, the proper method is assigned according to the characteristic of the local feature. For long edge region, the modified $NEDI(New Edge Directed Interpolation)^{[1]}$ method that interpolates long edge very well is used. The linear $filter^{[2]}$ that enhances high frequency components is used for complex edge, and the bilinear interpolation method is applied to flat region. The proposed method shows improved performance in PSNR and subjective evaluation compared with previous algorithms.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.93-96
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• 2000

In this paper, we present an improved novel interpolator that performs high quality interpolation on both synthetic and real world images. Its structure, which is based on a four directional linear predictor with equiripple windowed samples and phase matching equalizer, provides edge-directional data interpolation so that sharp and artifacts-free images are obtained at a reasonable computational cost.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10C
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• pp.1000-1009
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• 2007

This paper presents a content adaptive interpolation (CAI) for intra deinterlacing. The CAI consists of three steps: pre-processing, content classification, and adaptive interpolation. There are also three main interpolation methods in our proposed CAI, i.e. modified edge-based line averaging (M-ELA), gradient directed interpolation (GDI), and window matching method (WMM). Each proposed method shows different performances according to spatial local features. Therefore, we analyze the local region feature using the gradient detection and classify each missing pixel into four categories. And then, based on the classification result, a different do-interlacing algorithm is activated in order to obtain the best performance. Experimental results demonstrate that the CAI method performs better than previous techniques.

• ETRI Journal
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• v.30 no.4
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• pp.506-515
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• 2008

The H.264/AVC standard has adopted new coding tools such as intra-prediction, variable block size, motion estimation with quarter-pixel-accuracy, loop filter, and so on. The adoption of these tools enables an H.264/AVC-coded bitstream to have more information than was possible with previous standards. In this paper, we propose an effective spatial error concealment method with low complexity in H.264/AVC intra-frame. From information included in an H.264/AVC-coded bitstream, we use prediction modes of intra-blocks to recover a damaged block. This is because the prediction direction in each prediction mode is highly correlated to the edge direction. We first estimate the edge direction of a damaged block using the prediction modes of the intra-blocks adjacent to a damaged block and classify the area inside the damaged block into edge and flat areas. Our method then recovers pixel values in the edge area using edge-directed interpolation, and recovers pixel values in the flat area using weighted interpolation. Simulation results show that the proposed method yields better video quality than conventional approaches.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.68-77
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• 2009

A single field deinterlacing method, namely interpolation algorithm derived from low resolution (ILR), is presented in this paper. Traditional deinterlacing methods usually employ edge-based interpolation technique within pixel-based estimation. However, edge-based methods are somehow sensitive to noise and intensity variation in the image. Moreover, the methods are not satisfied in deciding the exact edge direction which controls the performance of the interpolation. In order to reduce the sensitivity, the proposed algorithm investigates low-resolution characteristics of the pixel to be interpolated, and applies it to high-resolution image. Simulation results demonstrates that the proposed method gives not only a better objective performance in terms of PSNR results compare to conventional edge-based interpolation methods, but also better subjective image quality.