오류 정정기능이 내장된 6-비트 70MHz 새로운 Interpolation-2 Flash ADC 설계

박정주,조경록 대한전자공학회 2004 電子工學會論文誌-SD (Semiconductor and devices) Vol.41 No.3

본 논문에서는 새로운 interpolation-2 방식의 비교기 구조를 제안하여 칩 면적과 전력 소모를 줄이며 오류정정 회로를 내장하는 6-비트 70㎒ ADC를 설계하였다. Interpolation 비교기를 적용하지 않은 flash ADC의 경우 2n개의 저항과 2n -1개의 비교기가 사용되며 이는 저항의 수와 비교기의 수에 비례하여 많은 전력과 큰 면적을 필요로 하고 있다. 또한, interpolation-4 비교기를 적용한 flash ADC는 면적은 작으나 단조도, SNR, INL, DNL 특성이 떨어진다는 단점이 있었다. 본 논문에서 설계한 interpolation-2 방식의 ADC는 저항, 비교기, 앰프, 래치, 오류정정 회로, 온도계코드 디텍터와 인코더로 구성되며, 32개의 저항과 31개의 비교기를 사용하였다. 제안된 회로는 0.18㎛ CMOS 공정으로 제작되어 3.3V에서 40mW의 전력소모로 interpolation 비교기를 적용하지 않은 flash ADC에 비해 50% 개선되었으며, 칩 면적도 20% 감소되었다. 또한 노이즈에 강한 오류정정 회로가 사용되어 interpolation-4 비교기를 적용한 flash ADC 에 비해 SNR이 75% 개선된 결과를 얻었다. In this thesis, a modified interpolation-2 6-bit 70MHz ADC is proposed minimizing chip area and power consumption, which includes an error correction circuit. The conventional flash ADC without interpolation comparators suffers from large chip area and more power consumption due to 2n resistors and 2n-1 comparators. Although the flash ADC with interpolation-4 comparators has small area, SNR, INL and DNL are degraded by comparison with the interpolation -2 comparator. We fabricated the proposed 6-bit ADC with interpolation-2 comparators using 0.18${\mu}{\textrm}{m}$ CMOS process. The ADC is composed of 32-resistors, 31 comparators, amplifiers, latches, error correction circuit, thermometer code detector and encoder As the results, power consumption is reduced to 40mW at 3.3V which is saving about 50% than a flash ADC without interpolation comparators, and area is reduced by 20%. SNR is increased by 75% in comparison with that of a flash ADC with interpolation-4 comparators.

소득집중도와 소득분포함수

윤종인 통계청 2018 통계연구 Vol.23 No.2

Piketty and Saez(2003), Kim(2012) estimate the top income shares by Pareto interpolation. We estimate the top income shares by Pareto and Lognormal interpolation. Also, to evaluate the performances of two interpolations, we estimate the top income shares of percentiles which is known, and then compare the estimated top income shares to the known top income share. If the estimated top income shares by Lognormal interpolation fits the known top income share better than those by Pareto interpolation, we can conclude that Lognormal intepolation is better than Pareto interpolation. Main results are as follows. First, estimates of the top income shares by Pareto and Lognormal interpolation show similar trends and have risen recently. Second, estimates of the top income shares by Lognormal interpolation are lower than those by Pareto interpolation. Third, the estimated top income shares by Lognormal interpolation fit the known top income shares better than those by Pareto interpolation. We conclude that estimates by Lognormal interpolation is better than those by Pareto interpolation but differences between them is not so large. Piketty and Saez(2003), 김낙년(2012)은 파레토 보간을 이용하여 소득집중도를 추정한다. 본 연구는 이에 더하여 자연대수 정규분포 보간을 이용하여 소득집중도를 추정하였다. 또한 두 보간법의 성과를 비교하기 위하여 다음과 같은 방법을 이용하였다. 우선 소득집중도가 알려진 소득계급에 대하여 두 보간법을 이용하여 소득집중도를 추정하였다. 그리고 두 보간법 중 어느 것이 알려진 소득집중도에 더 잘 부합하는가를 비교하였다. 주요 결과는 다음과 같다. 첫째, 파레토 보간과 자연대수 정규분포 보간을 이용하여 추정한 소득집중도의 추이는 크게 다르지 않았으며, 두 추정치 모두 최근까지 상승하였던 것으로 보인다. 둘째, 파레토 보간을 이용한 소득집중도 추정치는 자연대수 정규분포를 이용한 추정치보다 크다. 셋째 자연대수 정규분포 보간을 이용한 소득집중도 추정치가 파레토 보간을 이용한 것보다 실제 소득집중도에 더 잘 부합하는 것으로 나타났다. 따라서 소득집중도를 추정하는 방법으로는 자연대수 정규분포 보간이 더 좋은 방법이라고 판단된다. 그럼에도 불구하고 파레토 보간을 이용한 소득집중도가 크게 과대 추정되었다고 보기는 어렵다.

A Novel Image Interpolation Algorithm Based on Directional Extension of AP-DCT Interpolation Kernel

Zhonglin Ding,Li Li 보안공학연구지원센터 2014 International Journal of Signal Processing, Image Vol.7 No.5

In order to decrease the smoothing effect of traditional linear interpolation methods and avoid the complexity of edge-directed adaptive algorithms, a novel image interpolation algorithm based on the directional extension of linear interpolation kernel is proposed. At first, All Phase Non-subsampled Contourlet Transform is used to divide the image of low resolution into different frequencies and directional sub-band images, and then the All Phase Discrete Cosine Transform Interpolation Kernel is extended to 2-D with distinct directional priorities and used to enlarge respective sub-band images. The interpolated sub-band images are finally synthesized as the upsampled image. Simulation results demonstrate that the proposed algorithm improves both the subjective and objective quality of the interpolated images over conventional linear interpolation. The computation complexity of the proposed algorithm is moderate and it can be implemented with parallel structure so as to save more computation time.

Quadrilateral Irregular Network for Mesh-Based Interpolation

김태범,이치형 대한지질공학회 2023 지질공학 Vol.33 No.3

Numerical analysis has been adopted in nearly all modern scientific and engineering fields due to the rapid and ongoing evolution of computational technology, with the number of grid or mesh points in a given data field also increasing. Some values must be extracted from large data fields to evaluate and supplement numerical analysis results and observational data, thereby highlighting the need for a fast and effective interpolation approach. The quadrilateral irregular network (QIN) proposed in this study is a fast and reliable interpolation method that is capable of sufficiently satisfying these demands. A comparative sensitivity analysis is first performed using known test functions to assess the accuracy and computational requirements of QIN relative to conventional interpolation methods. These same interpolation methods are then employed to produce simple numerical model results for a real-world comparison. Unlike conventional interpolation methods, QIN can obtain reliable results with a guaranteed degree of accuracy since there is no need to determine the optimal parameter values. Furthermore, QIN is a computationally efficient method compared with conventional interpolation methods that require the entire data space to be evaluated during interpolation, even if only a subset of the data space requires interpolation.

Hybrid Algorithm for Interpolation Based on Macro-block Gray Value Gradient under H.264

왕실(Wang, Shi),진홍신(Chen, Hongxin),유현중(Yoo Hyun-Joong),김형석(Kim, Hyong-Suk) 한국산학기술학회 2009 한국산학기술학회논문지 Vol.10 No.2

H.264에서는 2-D 6-tap wiener filter가 1/2 화소의 위치로부터 1/4 화소 위치를 보간해 내는데 사용되고 있다. 이 방법은 비교적 간단하지만 이웃 화소들의 변화율을 무시하고, 4 방향의 이웃 화소들의 영향만 고려하게 되므로, 결과적으로 저역 필터의 특성을 갖게 된다. 그런데, 큐빅 보간 법을 사용하면 보다 넓은 영역의 화소 값을 고려하여 보간하는 장점은 있지만 계산이 복잡하다는 단점이 있다. 이 연구에서는 H.264에서 bilinear와 cubic 보간 법을 사용할 경우의 특성들을 해석하여, 임의의 큰 블록에 보다 적합한 보간 방법을 자동 선택할 수 있도록 하였다. 실험에서 물체영상의 움직임 탐색과 보간에 요구되는 계산 량을 보간의 정밀화를 통하여 대폭 감소시킬 수 있음을 보였다. H.264 suggests applying a 2-D 6-tap wiener filter to realize the interpolation for half-pixel positions, followed by a bilinear interpolation to get the data of quarter-pixels precision. This method is comparatively simpler; however, it only considers the affection of 4-connection neighborhood ignoring the influence that comes from the changing rate between respective neighborhoods. As a result, it has the characteristics of a Low-pass filter under the risk of losing high-frequency weights. The Cubic interpolation uses the gray-values within the larger regions of points to be sampled for interpolation. Nevertheless, the cubic interpolation is more complicated and computational. We give a deep analysis on the features while applying both bilinear and cubic interpolation in H.264 presenting a proper selection of interpolation algorithm with respect to specific distribution of gray-value in a certain grand block. The experiments point out that load for motion searching and interpolation are reduced when promoting the precision of interpolation simultaneously.

Image Interpolation Based on Saliency Information

보안공학연구지원센터(IJSIP) 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.10

In this paper, we propose an image interpolation algorithm based on the characteristics of the Human Visual System (HVS). Firstly, the saliency map is extracted for the input image by the feature contrast. Based on the saliency detection algorithm, the input image can be divided into salient regions and non-salient regions. A non-local means based interpolation and the bicubic interpolation operations are adopted to implement the image interpolation for salient and non-salient regions in visual scenes, respectively. Experimental results show that the proposed method improves the perceptual quality of the salient regions during image interpolation. The PSNR and SSIM results demonstrate that the proposed method can obtain better performance than existing related image interpolation methods.

모델 제약조건이 적용된 MWNI (Minimum Weighted Norm Interpolation)를 이용한 트레이스 내삽

최지현 ( Jihyun Choi ),송영석 ( Youngseok Song ),최지훈 ( Jihun Choi ),변중무 ( Joongmoo Byun ),설순지 ( Soon Jee Seol ),김기영 ( Kiyoung Kim ),이정모 ( Jeongmo Lee ) 한국지구물리·물리탐사학회 2017 지구물리와 물리탐사 Vol.20 No.2

MWNI (Minimum Weighted Norm Interpolation)를 이용한 내삽 방법은 고차원으로 확장이 용이하고 상대적으로 계산 속도가 빠르다는 장점을 가지고 있으나 알리아스 효과가 존재하는 자료의 내삽에 취약하다. 이런 문제의 개선을 위해 제안된 방법이 모델제약(model-constrained) MWNI이다. 이 논문에서는 MWNI를 이용한 방법과 모델제약 MWNI방법의 두가지 모듈을 개발한 후 알리아스 효과가 존재하는 자료의 내삽 결과를 비교하였다. 시공간 영역(t-x domain)과 주파수-파수 영역( f-k domain)의 결과 그림을 통해서 모델제약 MWNI를 적용했을 때의 결과가 더 효과적임을 확인할 수 있었다. 동해 울릉분지의 가스 하이드레이트 부존 지역의 현장 자료에 내삽을 적용한 결과, 가스침니 구간 전후로 진폭이 급격하게 변하는 자료에서도 내삽이 가능함을 확인할 수 있었다. 또한 매우 불규칙하고 넓은 구간에서 누락된 인공지진파 자료의 정규화를 통해 신호의 연결성 향상이 가능함을 보일 수 있었다. 결과적으로 이 논문에서 개발된 모듈은 현장의 다양한 여건에 의해 불규칙하거나 넓은 간격으로 얻어진 탄성파 자료의 정규화나 내삽에 효율적으로 활용될 수 있음을 확인하였다. For efficient data processing, trace interpolation and regularization techniques should be antecedently applied to the seismic data which were irregularly sampled with missing traces. Among many interpolation techniques, MWNI (Minimum Weighted Norm Interpolation) technique is one of the most versatile techniques and widely used to regularize seismic data because of easy extension to the high-order module and low computational cost. However, since it is difficult to interpolate spatially aliased data using this technique, model-constrained MWNI was suggested to compensate for this problem. In this paper, conventional MWNI and model-constrained MWNI modules have been developed in order to analyze their performance using synthetic data and validate the applicability to the field data. The result by using modelconstrained MWNI was better in spatially aliased data. In order to verify the applicability to the field data, interpolation and regularization were performed for two field data sets, respectively. Firstly, the seismic data acquired in Ulleung Basin gas hydrate field was interpolated. Even though the data has very chaotic feature and complex structure due to the chimney, the developed module showed fairly good interpolation result. Secondly, very irregularly sampled and widely missing seismic data was regularized and the connectivity of events was quite improved. According to these experiments, we can confirm that the developed module can successfully interpolate and regularize the irregularly sampled field data.

새로운 거리 가중치와 지역적 패턴을 고려한 적응적 선형보간법

김태양,전영균,정제창,Kim, Tae-Yang,Jeon, Yeong-Gyun,Jeong, Je-Chang 한국통신학회 2006 韓國通信學會論文誌 Vol.31 No.12C

영상 보간은 영상 처리 분야에서 전통적으로 많이 연구되어 왔고 널리 사용되고 있다. 그에 따라 다양한 보간 능력과 계산 복잡도를 갖는 보간법들이 많이 시도되고 있다. 이 논문에서는 기존의 선형 보간법을 위한 새로운 거리 가중치 개념과 보간되는 값의 상하, 좌우 지역적 패턴을 고려하여 반영하는 적응적 선형 보간법(New Adaptive Linear Interpolation : NAL Interpolation)을 제안한다. 새로운 거리 가중치는 기존의 거리에 선형적으로 비례하는 가중치의 개념에서 벗어나 가까운 화소에 더욱 더 영향을 많이 받는 특성을 이용하여 거리 가중치를 2차, 3차 다항식으로 개선한 것이다. 또한 NAL 보간법은 보간되는 화소의 상하, 좌우 패턴을 고려하는 선형 보간법으로 MF(magnification factor)의 변화에 따라 보다 선명한 이미지를 쉽게 얻기 위해서 보간하기 전 MF에 따라 패턴을 반영하는 정도를 결정하는 패턴 가중치를 이용한다. 실험 결과에서 제안된 보간법은 계산 복잡도 면에서 기존의 bicubic 보간법 보다 훨씬 간단할 뿐만 아니라 더 좋은 PSNR(peak signal-to-noise ratio)를 갖고 보다 선명한 화질의 영상으로 보간하였다. Image interpolation has been widely used and studied in the various fields of image processing. There are many approaches of varying complexity and robustness. In this paper, a new distance weight is proposed for the conventional linear interpolation. In comparison with the conventional linear weight, the new distance weight uses a quadratic or cubic polynomial equation to reflect that the interpolated value should be influenced more by the value of closer pixels in an input image. In this paper, the new adaptive linear (NAL) interpolation, which considers patterns near the interpolated value, is also proposed. This algorithm requires a pattern weight, which is used to determine the ratio of reflection on local patterns, to obtain an interpolated image that exhibits better quality at various magnification factors (MF). In the computer simulation, not only did the NAL interpolation exhibit much lower computational complexity than conventional bicubic interpolation, it also improved peak signal-to-noise ratios (PSNR).

인공신경망을 이용한 해양관측자료 보간 기법 소개

주현석(Hyun Seok Joo),김국진(Kuk Jin Kim),한진현(Jin Hyun Han),김영택(Young Taeg Kim) 전남대학교 수산과학연구소 2020 수산과학연구소논문집 Vol.28 No.2

In the framework of “The Comprehensive Data Analysis for Areas under the National Jurisdiction” Project, the Korea Hydrographic and Oceanographic Agency first checks data for missing or wrong values, then provides the data to the public. For stationary observation points, removing wrong or missing values entails temporal discontinuity which may not be best restored with interpolation. Manual correction is time-consuming and the decision criteria may differ among employees. The less is the quality of the data, the more specialists are to be involved, and the less objective are the models’ outcomes that use the data as an input. The focus of the current study is to overcome this by a temporal and spatial interpolation of marine data using neural networks. The experiments were done in two cases: an interpolation based on the single observation point data, and an interpolation based on the neighborhood observation points’ data. Then, each case was further subdivided into an interpolation based on six and twelve-hours time horizons. This is because, the variation in data is not large for the data within an hour timeframe, so simple nearest interpolation or linear interpolation models are sufficient. On the basis of this, the feasibility of interpolation of missing marine data was verified.

Image enhancement for computed tomography using directional interpolation for sparsely-sampled sinogram

Kim, Hui-Gyeong,Yoo, Hoon Elsevier 2018 Optik Vol.166 No.-

<P><B>Abstract</B></P> <P>This paper presents an image enhancement for computed tomography (CT) using a directional sparsely-sampled sinogram interpolation. In CT scanning, radiation exposure to human tissues needs to be minimized. Naturally reducing radiation dose has been discussed in various approaches. Among them, a sparsely-sampled sinogram is an effective approach to minimize radiation dose itself in CT scanning. However, less radiation in CT scanning provide a poor image quality since reconstructed images suffer from the streak artifact due to lack of X-ray views. To reduce the streak artifact, an efficient sinogram interpolation method needs to be studied. In this paper, to enhance image quality, we propose a novel sinogram interpolation based on directional information. To do this, a directional interpolation from deinterlacing is introduced and applied to sinogram interpolation efficiently. To evaluate the proposed method, experiments with a simulated phantom and clinical CT images are carried out. The results indicate that the proposed sinogram interpolation method outperforms the existing interpolation methods in terms of image quality.</P>