• Journal of Broadcast Engineering
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• v.17 no.6
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• pp.1048-1060
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• 2012

In this paper, an adaptive temporal and spatial filter (ATSF) based on mean square error (MSE) estimation is proposed. ATSF is a block based de-noising algorithm. Each noisy block is selectively filtered by a temporal filter or a spatial filter. Multi-hypothesis motion compensated filter (MHMCF) and bilateral filter are chosen as the temporal filter and the spatial filter, respectively. Although there is no original video, we mathematically derivate a formular to estimate the real MSE between a block de-noised by MHMCF and its original block and a linear model is proposed to estimate the real MSE between a block de-noised by bilateral filter and its original block. Finally, each noisy block is processed by the filter with a smaller estimated MSE. Simulation results show that our proposed algorithm achieves substantial improvements in terms of both visual quality and PSNR as compared with the conventional de-noising algorithms.

• Journal of Broadcast Engineering
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• v.12 no.5
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• pp.503-515
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• 2007

A new fast motion estimation algorithm is presented in this paper. The algorithm, named Enhanced Cross-Diamond Search (ECDS), is based on the Diamond Search (DS) algorithm. The DS algorithm, even though faster than the most well-known algorithms, was found not to be very robust in terms of objective and subjective qualities for several sequences and the algorithm searches unnecessary candidate blocks. We propose a novel ECDS algorithm using a small cross search as the initial step, and large/small DS patterns as subsequent steps for fast block motion estimation. Experimental results show that the ECDS is much more robust, provides a faster searching speed, and smaller distortions than other popular fast block-matching algorithms.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.8-14
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• 2017

Deinterlacing is a method to convert interlaced video, including two fields (even and odd), to progressive video. It can be divided into spatial and temporal methods. The deinterlacing method in the spatial domain can easily be hardware-implemented, but yields image degradation if information about the deinterlaced pixel does not exist in the same field. On the other hand, the method in the temporal domain yields a deinterlaced image with higher quality but uses more memory, and hardware implementation is more difficult. Furthermore, the deinterlacing method in the temporal domain degrades image quality when motion is not estimated properly. The proposed method is for deinterlacing in the spatial domain. It uses several deinterlacing methods according to statistical characteristics in neighboring pixel locations. In this procedure, the proposed method uses the C4.5 algorithm, a typical classification algorithm based on entropy for choosing optimal methods from among the candidates. The simulation results show that the proposed algorithm outperforms previous deinterlacing methods in terms of objective and subjective image quality.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.3
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• pp.93-102
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• 2008

In this paper, we propose a rate control algorithm for constant quality real time video coding. To achieve constant quality, previous algorithm exploit mean absolute of difference(MAD) as measure of frame complexity. However, if scene is abruptly changed or if quantization parameter is not constant, encoder produces various output bits with same MAD. Therefore we know that MAD does not appropriately reflect characteristic of frame. To solve this problem, we exploit model parameter as measure of frame complexity. Because model parameter means slope between output bits and MAD, it reflects correctly complexity of frame. And because previous model, R-MAD model, is not considered quantization parameter, as quantization parameter increases or decreases, model parameter of frame also vary. So model parameter obtained using previous model cannot reflect internal characteristic of video. We solve this problem using proposed model, which is considered quantization parameter. Experiment results show that our algorithm provide better performance, in terms of quality smoothness than previous algorithm. Especially, when scene is abruptly changed, our algorithm alleviates quality drop.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.865-869
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• 2009

An image resolution enhancement is mainly utilized as pre-processing technique for various image processing application. It requires to decrease image quality deterioration such as blurring. In this paper, we propose an image resolution enhancement algorithm using low level interpolation. In the proposed algorithm, we calculate an error using low level interpolation, estimate an error image from the calculated error. The estimated error image is added interpolated high resolution image, it become lastly reconstruction image. Our experiments obtained the average PSNR about 1dB which is improved results better than conventional method for sensitive image quality. Also, subjective image quality with edge region is more clearness. The proposed method may be helpful for applications in various multimedia systems such as image restoration.

• Journal of Korea Multimedia Society
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• v.14 no.8
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• pp.1000-1009
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• 2011

Image interpolation is a technique which estimates the non-allocated pixel values on image scale-transform. It requires minimum computational complexity and minimum image quality degradation on the interpolated resultant images. In this paper we propose an image interpolation method using iterative error estimation. The proposed method consists of the following five steps: loss-information computational step, loss-information estimation step, loss-information application step, error computation step, and error application step. The experimental results obtained show that the average PSNR is increased by 3.3dB, subjective image quality is enhanced and the minimum computation complexity is decreased by 83%. The proposed image interpolation algorithm may be helpful in various applications such as image reconstruction and enlargement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1684-1690
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• 2003

In this paper, we proposed a fuzzy controller for the evaluation of the quantization Parameters in the H.263 coder to optimize the subjective quality of each coded frame, keeping the transmission rate constant. We adopted the Mamdani method for fuzzification and the centroid method for defuzzification. The energy and entropy are correlated to features of the HVS in spatial domain, while motion vectors are used to estimate the temporal characteristics of the signal. And then, the fuzzy inputs adapted the variance and the entropy in spatial domain, and the motion vector in temporal domain. We induced the fuzzy membership function and decided the fuzzy relevance to be compatible in visual characteristics. And then, we designed FAM banks. The fuzzy technology has been applied to a practical video compression. This results is obtained an effective rate control technique, an optimum bit allocation and a high subjective quality using fuzzy quantization.

• Journal of the Korea Society of Computer and Information
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• v.19 no.8
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• pp.45-54
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• 2014

In this paper, we proposed an effective quality improvement scheme of magnified image using the surface characteristics in image. If the surface in image is estimated as simple convex surface or simple concave surface, the interpolated value can be calculated to have the surface characteristics by using the other method in the proposed scheme. The calculated value becomes the interpolated pixel value inmagnified image. So, themagnified image reflects the surface characteristics of the real image. If the surface is not estimated as simple convex surface or simple concave surface, the interpolated value is calculated more accurately than bilinear interpolation by using the method of the proposed scheme. The PSNR values of the magnified images using the proposed schemes are greater than those of the magnified images using the previous interpolation schemes.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.200-209
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• 2016

This paper proposes a non-uniform de-blur algorithm using IMU sensor and a long/short exposure-time image pair to efficiently remove the blur phenomenon. Conventional blur kernel estimation algorithms using sensor information do not provide acceptable performance due to limitation of sensor performance. In order to overcome such a limitation, we present a kernel refinement step based on images having different exposure times which improves accuracy of the estimated kernel. Also, in order to figure out the phenomenon that conventional non-uniform de-blur algorithms suffer from severe degradation of visual quality in case of large blur kernels, this paper a homography-based residual de-convolution which can minimize quality degradation such as ringing artifacts during de-convolution. Experimental results show that the proposed algorithm is superior to the state-of-the-art methods in terms of subjective as well as objective visual quality.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.244-247
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• 2010

현대 사회에서 영상 콘텐츠 (contents)의 사용량이 급증함에 따라 영상압축 기술은 이동통신이나 DMB 등의 시스템에 필수적인 기술이 되었으며 이에 따라 MPEG-x와 H.26x 등 국제적인 표준들이 존재한다. 전역 탐색 알고리듬은 주어진 검색 범위(search range) 내에서 모든 후보들의 변위의 에러 기준에 따라 최솟값을 이용해 위치를 검색하는 알고리듬이다. 그러나 전역 탐색 알고리듬은 각 화소에 대해 엄청난 양의 계산 로드를 가지며 이로 인해 심각한 문제를 발생시키는 단점이 있다. 1비트 변환 (one-bit transform) 을 이용한 고속 움직임 추정 알고리듬은 참조 프레임과 현재 프레임을 1비트, 즉 0 또는 1만 갖는 값으로 변환하는데, 이에는 exclusive-OR 연산을 통해 블록 매칭 에러 (block matching error)를 계산하는 과정과 변환하는 과정이 포함된다. 본 논문에서는 다양한 커널 (kernel)들을 이용한 1비트 변환과 움직임 추정에 대해 다루었으며, 기존에 있었던 1비트 변환에 이용된 커널과는 다른 다양한 커널을 이용한 움직임 추정 결과들을 비교해봄으로써 화질열화를 최소로 하는 커널을 찾는 것에 대해 연구했다.