• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.707-718
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• 2008

We derive a modified version of the cubic convolution scaler to enlarge or reduce the size of digital image with arbitrary ratio. To enhance the edge information of the scaled image and to obtain a high-quality scaled image, the proposed scaler is applied along the direction of an edge. Since interpolation along the direction of an edge has to process nonuniformly sampled data, the kernel of the cubic convolution scaler is modified to interpolate the data. The proposed scaling scheme can be used to resize pictures in various formats in a transcoding system that transforms a bit stream compressed at one bit rate into one compressed at another bit rate. In many applications, such as transcoders, the resolution conversion is very important for changing the image size while maintaining high quality of the scaled image. We show experimental results that demonstrate the effectiveness of the proposed interpolation method. The proposed scheme provides clearer edges, without artifacts, in the resized image than do conventional schemes. The algorithm exhibits significant improvement in the minimization of information loss when compared with the conventional interpolation algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.9C
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• pp.867-880
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• 2007

We derive a modified version of cubic convolution interpolation for the enlargement or reduction of digital images by arbitrary scaling factors. The proposed scaling scheme is used to resize various format pictures in the transcoding system, which transforms the bitstream compressed at a bit rate, such as the HD bitstream, into another bit rate stream. In many applications such as the transcoder, the resolution conversion is very important for changing the image size while the scaled image maintains high quality. We focus on the modification of the scaler kernel according to the relation between formats of the original and the resized image. In the modification, various formats defined in MPEG standards are considered. We show experimental results that demonstrate the effectiveness of the proposed interpolation method.

• Journal of Korea Multimedia Society
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• v.10 no.7
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• pp.838-845
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• 2007

In this paper, we propose a modified cubic convolution scaler for the enlargement or reduction of digital images. The proposed method has less computational complexity than the cubic convolution method. In order to reduce the computational complexity, we use the linear function of the cubic convolution and the difference value of adjacent pixels for selecting interpolation methods. We employ adders and barrel shifts to calculate weights of the proposed method. The proposed method is compared with the conventional one for the computational complexity and the image quality. It has been designed and verified by HDL(Hardware Description Language), and synthesized using Xilinx Virtex FPGA.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.122-124
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• 2014

보간 기법은 영상의 해상도를 변경하는 것이다. 멀티미디어 기기의 해상도가 다양하기 때문에 원 영상은 각각에 맞는 해상도로 변경되어야 한다. 해상도 변경은 존재하지 않는 값을 임의로 만들어 채우는 것이기 때문에 왜곡이 발생한다. 대부분의 scaler에서는 수평과 수직 방향으로 해상도 변경을 하는데, 이 때문에 edge 영역에서는 왜곡이 더 많이 발생하며 쉽게 눈에 띈다. 본 논문에서는 edge 방향에서 발생하는 왜곡을 극복하기 위해 영상의 edge 정보와 Cubic Convolution을 이용해 임의의 배율로 해상도를 변경하는 방법을 제안한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.11a
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• pp.12-15
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• 2013

최근 UHD TV 출시와 HD급 영상의 보편화로 영상에 대한 해상도 변경 기술의 중요성이 높아지고 있다. 본 논문에서는 기존의 cubic convolution 기법을 응용하여, 영역별 특성에 따라 적응적인 가변 커널 길이의 cubic convolution으로 화면 해상도를 변환하는 기법을 제안한다. 제안하는 기법은 영상의 화질을 개선시키면서도 상황에 따라 하드웨어의 line memory를 절약할 수 있도록 설계를 하여 화질 개선뿐만이 아니라 하드웨어적으로도 더 효율적으로 사용이 가능하다. 또 tuning parameter 를 최적화 하는 방법을 통해 기존의 cubic convolution 기법보다 더 좋은 화질의 영상을 얻을 수 있다.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.112-118
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• 2014

As higher quality of image is required for digital image scaling, longer processing time is required. Therefore the technology that can make higher quality image quickly is needed. We propose the double linear-cubic convolution interpolation which creates the high quality image with low complexity and hardware resources. The proposed interpolation methods which are made up of four one-dimensional linear interpolations and one one-dimensional cubic convolution perform linear-cubic convolution interpolation in horizontal and vertical direction. When compared in aspects of peak signal-to-noise ratio(PSNR), performance time and amount of hardware resources, the proposed interpolation provided better PSNR, low complexity and less hardware resources than bicubic convolution interpolation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.11a
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• pp.143-146
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• 2013

멀티미디어 시대에 있어 이미지 신호처리(Image Signal Processing, ISP) 기술의 중요성이 거듭 강조되고 있는 가운데, 디지털 신호의 해상도를 변경하기 위해 여러 가지 커널을 사용하여 영상을 scaling 하는 방법들이 제안되고 있다. 본 논문에서 는 cubic convolution scaler를 이용하여 영상을 확대 및 축소할 때 하드웨어 관점에서의 메모리 최적화를 주제로 다룬다. SoC 상에서는 라인 메모리 개념을 가지기 때문에 영상의 해상도를 변환할 때 많은 메모리를 사용하게 된다. 또한 scaling을 할 때 곱하기 연산이 들어가게 되면 그에 비례하여 복잡도와 그에 따른 비용이 증가하게 된다. 이에 메모리와 process단계를 최적화하는 방법을 제안한다.

• Journal of Broadcast Engineering
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• v.10 no.3
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• pp.270-285
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• 2005

A joint design scheme is proposed to optimize the up/down scaler and the motion vector estimation module in the transcoder system. The proposed scheme first optimizes the resolution scaler for a fixed motion vector, and then a new motion vector is estimated for the fixed scaler. These two steps are iteratively repeated until they reach a local optimum solution. In the optimization of the scaler, we derive an adaptive version of a cubic convolution interpolator to enlarge or reduce digital images by arbitrary scaling factors. The adaptation is performed at each macroblock of an image. In order to estimate the optimal motion vector, a temporary motion vector is composed from the given motion vectors. Then the motion vector is refined over a narrow search range. It is well-known that this refinement scheme provides the comparable performance compared to the full search method. Simulation results show that a jointly optimized system based on the proposed algorithms outperforms the conventional systems. We can also see that the algorithms exhibit significant improvement in the minimization of information loss compared with other techniques.