• 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.

• Journal of Industrial Technology
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• v.28 no.A
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• pp.35-42
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• 2008

Recently, there are a lot of multimedia products to using image interpolation system. However, most interpolation systems in existence suffer visually to some extents the effects of blurred edges and jagged artifacts in the image. I in this paper, we propose the adaptive linear interpolation system that uses the sub-pixel. We system calculate the warped distance among the pixels of an image, and use data for Optimize length parameter. Our experimental results show that our new algorithm significantly outperforms linear interpolation in subjective quality, and in most cases, in terms of PSNR as well.

• Journal of Internet Computing and Services
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• v.9 no.1
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• pp.171-177
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• 2008

In this paper we compared the performance of interpolation algorithms for Bayer patterned image sensors under the various illumination intensities. As the interpolation algorithms, we used bilinear color interpolation and adaptive fuzzy color interpolation and our experimentation shows that performance of interpolation algorithms depend on the lighting conditions; in low intensity of illumination, bilinear color interpolation with median filter performs best, in high intensity of illumination, adaptive fuzzy color interpolation performs best, and in between bilinear color interpolation performs best. This study suggested an interpolation scheme which applies different interpolation algorithm according to the intensity of the input image, resuting in the better image quality.

• Journal of Industrial Technology
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• v.28 no.A
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• pp.27-34
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• 2008

The purpose of this paper is an adaptive image interpolation using parametric cubic convolution. Proposed method derive parameter of adapting the frequency from adjacent values. The parameter optimize the interpolation kernel of cubic convolution. Simulation results show that the proposed method is superior to the conventional method in terms of the subjective and objective image quality.

• 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 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.4
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• pp.795-798
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• 2007

In this paper, we propose an image reconstruction method utilizing an optimized adaptive interpolation kernel along with a 2D M-channel perfect reconstruction filter bank (M-ch PR-FB) structure. In particular, the proposed approach leads to construction of a sharper image than a direct conversion, still preserving high frequency components of the original image through the subband processing of the 2D M-ch PR-FB. Finally, the image quality of the proposed approach is demonstrated by comparing with those of the direct methods using conventional interpolation kernels.

• Journal of Korea Multimedia Society
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• v.9 no.8
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• pp.1000-1009
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• 2006

We propose an adaptive linear interpolation locating sub-pixels. We utilize a pixel-based parameter in the conventional linear interpolation. To optimally obtain the parameter, we propose a generic interpolation structure including a low pass filter and minimum mean square error. We also propose a simple version of the generic interpolation method, which obtain a closed-form solution. Simulation results show that the proposed method is superior to the state-of-the-art methods such as warped distance linear interpolation and shifted linear interpolation, as well as the conventional method such as the linear interpolation and the cubic convolution interpolation in terms of the subjective and objective image quality.

• 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.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.3
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• pp.128-134
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• 2014

A real-time, continuous-scale image interpolation method is proposed based on a bilinear interpolation with directionally adaptive low-pass filtering. The proposed algorithm was optimized for hardware implementation. The ordinary bi-linear interpolation method has blocking artifacts. The proposed algorithm solves this problem using directionally adaptive low-pass filtering. The algorithm can also solve the severe blurring problem by selectively choosing low-pass filter coefficients. Therefore, the proposed interpolation algorithm can realize a high-quality image scaler for a range of imaging systems, such as digital cameras, CCTV and digital flat panel displays.