• Journal of the Optical Society of Korea
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• 제17권5호
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• pp.405-409
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• 2013

In this paper, a unifying framework to evaluate the depth resolution of axially distributed image sensing (ADS) systems under fixed resource constraints is proposed. The proposed framework enables one to evaluate the system performance as a function of system parameters such as the number of cameras, the number of pixels, pixel size, and so on. The Monte Carlo simulations are carried out to evaluate ADS system performance as a function of system parameters. To the best of our knowledge, this is the first report on quantitative analysis of ADS systems under fixed resource constraints.

• 대한원격탐사학회지
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• 제32권1호
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• pp.49-60
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• 2016

This paper presents a set of methods to evaluate the image quality of smartphone cameras as compared with that of a DSLR camera. In recent years, smartphone cameras have been used broadly for many purposes. As the performance of smartphone cameras has been enhanced considerably, they can be considered to be used for precise mapping instead of metric cameras. To evaluate the possibility, we tested the quality of one DSLR camera and 3 smartphone cameras. In the first step, we compare the amount of lens distortions inherent in each camera using camera calibration sheet images. Then, we acquired target sheet images, extracted reference lines from them and evaluated the geometric quality of smartphone cameras based on the amount of errors occurring in fitting a straight line to observed points. In addition, we present a method to evaluate the radiometric quality of the images taken by each camera based on planar fitting errors. Also, we propose a method to quantify the geometric quality of the selected camera using edge displacements observed in target sheet images. The experimental results show that the geometric and radiometric qualities of smartphone cameras are comparable to those of a DSLR camera except lens distortion parameters.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1999년도 제29회 춘계학술대회
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• pp.147-155
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• 1999

The film thickness and shape of elastohydrodynamic lubrication is measured by optical interferometer, which is the most precise method for EHL film measurement. However the interpretation of the image pattern from optical viscometer is not easy for two-dimensional shape. A newly developed method of image processing makes it possible to evaluate the film thickness and shape in every point of contact region with two dimensional aspects. In this study, we captured film shape of EHL film from the monochromatic incident light with the Image processing method, which uses phase shift method, and obtained the image analysis method for gray level image in order to qualitatively evaluate film shapes.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.397-400
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• 2004

Synthetic Aperture Radar(SAR) is an active micro­wave instrument that performs high-resolution observation under almost all weather conditions. Although there are many advantages of SAR instrument, many complicated steps are involved in order to generate SAR image products. Many research and algorithms have been proposed to process radar signal and to increase the quality of SAR products. However, it is hard to find research which compare the quality of SAR products generated with different algorithms and processing methods. In our previous research, a SAR processing s/w was developed for a ground station. In addition, quality assessment procedures and their test parameters inside a SAR processor was proposed. The purpose of this paper is to evaluate the quality of SAR images generated from the developed SAR processing s/w. However, If there are no direct measurements such as radar reflector or scattering field measurement values it is difficult to compare SAR images generated with different methods. An alternative procedures and parameters for SAR image quality evaluation are presented and the problems involved in the comparison methods are discussed. Experiments based on real data have been conducted to evaluate and analyze quality of SAR images.

• 한국멀티미디어학회논문지
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• 제16권8호
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• pp.934-942
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• 2013

영상 크기 변환은 응용 환경에서의 다양한 목적을 위하여 사용되며, 변환 함수의 성능을 평가하기 위하여 처리전과 후의 두 영상의 화질을 비교한다. 변환 함수의 객관적 성능 평가를 위하여 화질 비교의 정확한 지표가 요구되며, 실제 다양한 관점에서의 접근이 이루어졌다. 하지만 영상 크기 변환 과정에서 생략되거나 새롭게 생성되는 화소들의 위치를 고려한 화질 비교 척도에 관한 연구는 거의 이루어지지 않고 있다. 따라서 본 논문에서는 영상 크기 변환에서 발생하는 화소들의 생략 및 추정 위치를 고려한 객관적 영상 화질 측정방법을 제안한다. 제안하는 방법은 기존의 영상 화질 척도를 이용하여 위치 변화를 고려한 새로운 영상화질 측정 방법을 만들고, 위치 변화에 대한 민감도를 평가하였다. 실험을 통해서 기존에 널리 사용되는 영상 화질 측정 방법이 화소들의 생략 및 추정 위치의 변화에 많은 영향을 받는 것을 알 수 있었고, 제안하는 방법이 화소들의 생략 및 추정 위치 변화를 고려한 영상 화질 표현의 객관적 척도임을 확인하였다. 제안하는 방법은 영상 복원 및 개선 함수의 성능을 평가하는 척도로서 유용하게 사용될 수 있다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.1268-1271
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• 2002

The major threat of geometric manipulations is that they change the positions of watermarks, therefore the detection process fails to extract watermark properly. Since they cause the same effects on the host image as watermarks simultaneously, evaluating the distorted host image can be helpful to measure the nature of distortions. In this paper, we propose a geometrical distortion-resilient watermarking algorithm based on this property. Firstly we evaluate the orientation of a host image by filtering it with directional Gabor kernels, then we insert embedding pattern aligned to the estimated orientation. In its detection step, we evaluate the orientation again by Gabor filtering, then simply project and average the projected value to obtain a 1-D projection average pattern. Finally, auto-correlation function of the 1-D projection average pattern identifies periodic peaks. Analysed are experimental results against geometrical attacks including aspect ratio changes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권1호
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• pp.288-307
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• 2016

Image distortions are typically characterized by degradations of structures. Dictionaries learned from natural images can capture the underlying structures in images, which are important for image quality assessment (IQA). This paper presents a general-purpose no-reference image quality metric using a GRadient-Induced Dictionary (GRID). A dictionary is first constructed based on gradients of natural images using K-means clustering. Then image features are extracted using the dictionary based on Euclidean-norm coding and max-pooling. A distortion classification model and several distortion-specific quality regression models are trained using the support vector machine (SVM) by combining image features with distortion types and subjective scores, respectively. To evaluate the quality of a test image, the distortion classification model is used to determine the probabilities that the image belongs to different kinds of distortions, while the regression models are used to predict the corresponding distortion-specific quality scores. Finally, an overall quality score is computed as the probability-weighted distortion-specific quality scores. The proposed metric can evaluate image quality accurately and efficiently using a small dictionary. The performance of the proposed method is verified on public image quality databases. Experimental results demonstrate that the proposed metric can generate quality scores highly consistent with human perception, and it outperforms the state-of-the-arts.

• 한국인쇄학회지
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• 제18권2호
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• pp.55-68
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• 2000

Joint photographic experts group (JPEG) is a standard still-image compression technique, established by the international organization for standardization (ISO) and international telecommunication standardization sector (ITUT). The standard is intended to be utilized in the various kinds of color still imaging systems as a standard color image coding format. Because JPEG is a lossy compression, the decompressed image pixel values are not the same as the value before compression. Various distortions of JPEG compression and JPEG recompression has been reported in various papers. The Image compressed by JPEG is often recompressed by same type compression method in JPEG. In general, JPEG is a lossy compression and the quality of compressed image is predicted that is varied in according to recompression Q-factor. In this paper, four difference color samples(photo image, gradient image, gradient image, vector drawing image, text image) were compressed in according to various Q-factor, and then the compressed images were recompressed according to various Q-factor once again. As the result, this paper evaluate the variation of image quality and file size in JPEG recompression and recommed the optimum recompression factor.

• 대한방사선기술학회지:방사선기술과학
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• 제44권6호
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• pp.655-661
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• 2021

Positron emission tomography (PET) images is affected by acquisition time, short acquisition times results in low gamma counts leading to degradation of image quality by statistical noise. Noise2Void(N2V) is self supervised denoising model that is convolutional neural network (CNN) based deep learning. The purpose of this study is to evaluate denoising performance of N2V for PET image with a short acquisition time. The phantom was scanned as a list mode for 10 min using Biograph mCT40 of PET/CT (Siemens Healthcare, Erlangen, Germany). We compared PET images using NEMA image-quality phantom for standard acquisition time (10 min), short acquisition time (2min) and simulated PET image (S2 min). To evaluate performance of N2V, the peak signal to noise ratio (PSNR), normalized root mean square error (NRMSE), structural similarity index (SSIM) and radio-activity recovery coefficient (RC) were used. The PSNR, NRMSE and SSIM for 2 min and S2 min PET images compared to 10min PET image were 30.983, 33.936, 9.954, 7.609 and 0.916, 0.934 respectively. The RC for spheres with S2 min PET image also met European Association of Nuclear Medicine Research Ltd. (EARL) FDG PET accreditation program. We confirmed generated S2 min PET image from N2V deep learning showed improvement results compared to 2 min PET image and The PET images on visual analysis were also comparable between 10 min and S2 min PET images. In conclusion, noisy PET image by means of short acquisition time using N2V denoising network model can be improved image quality without underestimation of radioactivity.

• 한국콘텐츠학회논문지
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• 제12권8호
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• pp.87-95
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• 2012

본 연구는 객관적인 화질 평가 요소들과 선호도를 기반으로 한 주관적 화질 평가 모형을 구축하여 감상자들의 화질에 대한 선호도를 객관적 요소들로 분석할 수 있도록 하였다. 즉 제조사들이 이해하기 쉬운 객관적 화질 평가 요소들을 선정하고, 이와 같은 요소들을 질문하는 문항을 기반으로 하여 사진의 품질을 평가하는 방식으로 주관적 화질 평가 모형을 구축하였다. 또한 화질 평가에 사용되는 실제 사진을 일반인들이 주로 촬영하는 장면인 인물사진으로 선택하여 실험결과의 일반화와 타당성을 추구하였다. 본 실험의 주관적 화질 평가 모형을 통하여 감상자들이 선호하는 화질을 평가하고 그 결과가 최종적인 사진의 선호도에 어떠한 상관관계를 갖으며 영향을 미치는지 분석하였다. 이와 같은 상관관계 분석을 통하여 감상자가 선호하는 화질에 대해 파악하고 화질을 향상시키는 요소를 분석할 수 있었다. 그 결과 선호도와 가장 상관관계가 높은 변수는 색재현력, 다이내믹 레인지, 노이즈, 해상도 순이었으며, 인물 사진 자극의 특성상 색재현력과 선호도가 가장 높은 수준의 상관관계를 보였다. 이러한 결과는 단순 수치화된 객관적 화질 평가 요소들을 언어로 확장시켜, 선호도에 기반을 둔 주관적 화질 평가 모형을 제시함으로써 일반 사용자와 제조사 모두가 쉽게 이해할 수 있는 새로운 방식의 접근이라고 할 수 있다.