• Journal of Korea Multimedia Society
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• v.20 no.10
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• pp.1655-1661
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• 2017

A high-speed directional interpolation algorithm based on the pattern of a $2{\times}2$ pixel block is proposed in this paper. The basic concept of the proposed algorithm is started from UDWT(un-decimated discrete wavelet transform), but there are no transform operations. In order to detect the direction of the edge, 4-pixel differences of two pairs in the $2{\times}2$ block are compared. The $2{\times}2$ block patterns are grouped into total 8 classes, and thereafter the directional interpolation is executed according to the type of the pattern. Since the calculation of the proposed algorithm is very simple and needs a few additions on integer data type, the computation time is almost same as that of bilinear interpolation algorithm. However, experimental results show that the output quality of the proposed one is better than those of the conventional interpolation ones in the objective quality and the computation time.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1479-1494
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• 2020

As an important part of image processing, image demosaicking has been widely researched. It is especially necessary to propose an efficient interpolation algorithm with good visual quality and performance. To improve the limitations of residual interpolation (RI), based on RI algorithm, minimalized-Laplacian RI (MLRI), and iterative RI (IRI), this paper focuses on adaptive RI (ARI) and proposes an improved ARI (IARI) algorithm which obtains more distinct R, G, and B colors in the images. The proposed scheme fully considers the brightness information and edge information of the image. Since the ARI algorithm is not completely adaptive, IARI algorithm executes ARI algorithm twice on R and B components according to the directional difference, which surely achieves an adaptive algorithm for all color components. Experimental results show that the improved method has better performance than other four existing methods both in subjective assessment and objective assessment, especially in the complex edge area and color brightness recovery.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2068-2086
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• 2011

Based on the quincunx sub-sampling grid, the New Interleaved Hierarchical INTerpolation (NIHINT) method is recognized as a superior pyramid data structure for the lossless and progressive coding of natural images. In this paper, we propose a new image interpolation algorithm, Edge Adaptive Hierarchical INTerpolation (EAHINT), for a further reduction in the entropy of interpolation errors. We compute the local variance of the causal context to model the strength of a local edge around a target pixel and then apply three statistical decision rules to classify the local edge into a strong edge, a weak edge, or a medium edge. According to these local edge types, we apply an interpolation method to the target pixel using a one-directional interpolator for a strong edge, a multi-directional adaptive weighting interpolator for a medium edge, or a non-directional static weighting linear interpolator for a weak edge. Experimental results show that the proposed algorithm achieves a better compression bit rate than the NIHINT method for lossless image coding. It is shown that the compression bit rate is much better for images that are rich in directional edges and textures. Our algorithm also shows better rate-distortion performance and visual quality for progressive image transmission.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.26-31
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• 2010

We proposed a new directional edge based interpolation, DEBI, by combining two weighted directional information to reduce blurred edges and annoying artifacts. Four isotropic gradient masks are employed in defining edge directions and they are proven to hold a first order derivative relation with respect to a rotating coordinate. Two minimum gradients among four absolute directional results are shown to be sufficient to describe slant edges efficiently. Compared with widely used bilinear and bicubic interpolation methods, the proposed algorithm results in a noticeable improvement along edge area.

• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1393-1401
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• 2014

This paper presents an adaptive image interpolation method using a pixel-based neighbor embedding which is modified from the patch-based neighbor embedding of contemporary super resolution algorithms. Conventional interpolation methods for high resolution detect at least 16-directional edges in order to remove zig-zaging effects and selectively choose the interpolation strategy according to the direction and value of edge. Thus, they require much computation and high complexity. In order to develop a simple interpolation method preserving edge's directional shape, the proposed algorithm adopts the simplest Haar wavelet and suggests a new pixel-based embedding scheme. First, the low-quality image but high resolution, magnified into 1 octave above, is acquired using an adaptive 8-directional interpolation based on the high frequency coefficients of the wavelet transform. Thereafter, the pixel embedding process updates a high resolution pixel of the magnified image with the weighted sum of the best matched pixel value, which is searched at its low resolution image. As the results, the proposed scheme is simple and removes zig-zaging effects without any additional process.

• 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.30 no.3C
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• pp.133-140
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• 2005

This paper introduces a spatial error concealment technique using directional interpolation in block-based compression. The first step involves finding the spatial direction vectors represented an edge-direction in the lost block using spatial boundary matching algorithm. Then, the error blocks are recovered by directional interpolation through these vectors and concealed by using the recovered blocks which have lower directional boundary matching error out of them relatively. This proposed method is able to deal with errors on macroblock or slice level adaptively. And it has lower complexity and maintains better performance compared to the conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2C
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• pp.124-131
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• 2007

This paper presents a block loss recovery technique for the image block data corrupted by transmission losses through the employment of fine directional interpolation (FDI). The proposed algorithm introduces a spatial direction vector (SDV). The SDVs are extracted from the edge information of the neighboring image data. Subsequently, the SDVs are adaptively applied to interpolate lost pixels on a pixel-by-pixel basis. This approach improves the capability to more reliably recover high-detailed contents in the corrupted block. Experimental results demonstrate that the FDI method performs better as compared to previous techniques.

• Proceedings of the IEEK Conference
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• 2000.06e
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• pp.138-141
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• 2000

In this paper, we present a new interpolation algorithm for three-dimensional images. Generally, Image interpolation is carried out along the three orthogonal coordinates. However, such a interpolation algorithm along orthogonal coordinates do not utilize the contour of 3 dimensional objects. In this paper, we propose a new directional interpolation algorithm that searches the best interpolation direction for 3-dimensional objects. Experiments with brain MR images show promising results.

• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.501-509
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• 2011

In this paper, we propose an edge profile adaptive bi-directional diffusion interpolation method which consists of shock filter and level set. In recent years many interpolation methods have been proposed but all methods have some degrees of artifacts such as blurring and jaggies. To solve these problems, we adaptively apply shock filter and level set method where shock filter enhances edge along the normal direction and level set method removes jaggies artifact along the tangent direction. After the initial interpolation, weights of shock filter and level set are locally adjusted according to the edge profile. By adaptive coupling shock filter with level set method, the proposed method can remove jaggies artifact and enhance the edge. Experimental results show that the average PSNR and MSSIM of our method are increased, and contour smoothness and edge sharpness are also improved.