• 대한전기학회논문지
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• 제37권4호
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• pp.240-250
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• 1988

This pc-vision system digitizes/displays 512*512*8 bit pixel image in real time and is capable of the various image processing. This system provides a versatile solution to those users pursuing high performance image processing system compatible with the VME bus, and is general purpose imaging system giving the optimal efficiency for machine vision, medical use and various task. In this paper, Image processing technique has classified image enhancement and image analysis in order to design and implement the pc-vision system. In order to improve processing speed, This system unilizing ROI processing performs point operation, local operation and global operation as well as common arithmetic/logic operation in real time.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2009년도 9th International Meeting on Information Display
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• pp.972-974
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• 2009

This paper presents smart regional contrast enhancement technique of partitioned image for local dimming backlight on small-sized mobile display to reach two goals. One is to save the power consumption, and the other to improve contrast ratio of display image. Recently new advanced method is proposed, named local dimming method, that backlight LED is positioned on backside of the display panel. So it is important to partition an image by sub blocks and then post-processing independantly. This means regional contrast enhancement. After partitioning, we compare the mean luminance(Y) value of each sub-block image with the one of original whole image. If some blocks have the mean value lower than the one of whole image, they are processed with the proposed method and others are bypassed. Simultaneously the information of the processed blocks are transferred to BLC(Backlight LED Controller). And then the supply current of each backlight LED is reduced to realize the contrast ratio enhancement and at the same time to power consumption reduction. In addition, we verify this proposed method is free from blocking artifacts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권1호
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• pp.436-450
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• 2017

Recently, the method based on fractional order partial differential equation has been used in image processing. Usually, the optional order of fractional differentiation is determined by a lot of experiments. In this paper, a denoising model is proposed based on adaptive fractional order anisotropic diffusion. In the proposed model, the complexity of the local image texture is reflected by the local variance, and the order of the fractional differentiation is determined adaptively. In the process of the adaptive fractional order model, the discrete Fourier transform is applied to compute the fractional order difference as well as the dynamic evolution process. Experimental results show that the peak signal-to-noise ratio (PSNR) and structural similarity index measurement (SSIM) of the proposed image denoising algorithm is better than that of other some algorithms. The proposed algorithm not only can keep the detailed image information and edge information, but also obtain a good visual effect.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1331-1346
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• 2018

Aiming at the problem that the gradient-based edge detection operators are sensitive to the noise, causing the pseudo edges, a triqubit-state measurement-based edge detection algorithm is presented in this paper. Combing the image local and global structure information, the triqubit superposition states are used to represent the pixel features, so as to locate the image edge. Our algorithm consists of three steps. Firstly, the improved partial differential method is used to smooth the defect image. Secondly, the triqubit-state is characterized by three elements of the pixel saliency, edge statistical characteristics and gray scale contrast to achieve the defect image from the gray space to the quantum space mapping. Thirdly, the edge image is outputted according to the quantum measurement, local gradient maximization and neighborhood chain code searching. Compared with other methods, the simulation experiments indicate that our algorithm has less pseudo edges and higher edge detection accuracy.

• Journal of Information Processing Systems
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• 제13권2호
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• pp.305-320
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• 2017

The selection of subset size is of great importance to the accuracy of digital image correlation (DIC). In the traditional DIC, a constant subset size is used for computing the entire image, which overlooks the differences among local speckle patterns of the image. Besides, it is very laborious to find the optimal global subset size of a speckle image. In this paper, a self-adaptive and bidirectional dynamic subset selection (SBDSS) algorithm is proposed to make the subset sizes vary according to their local speckle patterns, which ensures that every subset size is suitable and optimal. The sum of subset intensity variation (${\eta}$) is defined as the assessment criterion to quantify the subset information. Both the threshold and initial guess of subset size in the SBDSS algorithm are self-adaptive to different images. To analyze the performance of the proposed algorithm, both numerical and laboratory experiments were performed. In the numerical experiments, images with different speckle distribution, different deformation and noise were calculated by both the traditional DIC and the proposed algorithm. The results demonstrate that the proposed algorithm achieves higher accuracy than the traditional DIC. Laboratory experiments performed on a substrate also demonstrate that the proposed algorithm is effective in selecting appropriate subset size for each point.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1329-1331
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• 2003

Improvement of the classification accuracy is one of the major concerns in the field of remote sensing application research in recent years. Previous research shows that the accuracy of the conventional classification methods based only on the original spectral information were usually unsatisfied and need to be refined by manual edit. This present paper describes a method of combining the image processing, ancillary data (such as digital elevation model) and expert knowledge (especially the knowledge of local professionals) to improve the efficiency and accuracy of the satellite image classification in hilly land. Firstly, the Landsat TM data were geo-referenced. Secondly, the individual bands of the image were intensitynormalized and the normalized difference vegetation index (NDVI) image was also generated. Thirdly, a set of sample pixels (collected from field survey) were utilized to discover their corresponding DN (digital number) ranges in the NDVI image, and to explore the relationships between land use type and its corresponding spectral features . Then, using the knowledge discovered from previous steps as well as knowledge from local professionals, with the support of GIS technology and the ancillary data, a set of conditional statements were applied to perform the TM imagery classification. The results showed that the integration of image processing and spatial analysis functions in GIS improved the overall classification result if compared with the conventional methods.

• 융합신호처리학회논문지
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• 제11권3호
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• pp.189-196
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• 2010

본 논문에서는 이미지 센서에 의해 발생하는 노이즈를 제거하기 위한 적응적 로컬 시그마 필터 장치를 제안하였다. 이미지 센서에 의해 발생하는 작은 노이즈는 이미지 센서의 아날로그 게인과 노출시간의 증가로 인해 영상 정보와 함께 증폭되며 이러한 노이즈 제거를 목표로 시스템을 설계 하였다. Flatness Index Map 알고리즘을 사용해 영상의 윤곽선을 추출하였으며, 임계치가 영상의 휘도에 따라 적응적으로 변화하도록 설계하여 고조도 영상에서는 윤곽선 추출을 수행하지 않으며, 저조도에서만 윤곽선을 추출하도록 하였다. 추출된 윤곽선을 판단하여 그에 해당하는 픽셀에 대해서만 Local Sigma Filter 알고리즘을 사용하여 노이즈 제거를 수행 하였다. 설계된 필터의 성능 검증을 위해 윈도우 테스트 프로그램을 제작하였다. 그리고 HDL을 사용해 하드웨어로 설계하였으며, FPGA Demonstration board와 $1280{\times}720$ 이미지 사이즈, 30 frame/sec의 성능을 갖는 HD급 CMOS 이미지 센서를 사용해 하드웨어로 설계된 로컬 시그마 필터의 동작을 검증하였다.

• 한국통신학회논문지
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• 제17권8호
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• pp.891-897
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• 1992

본 논문은 일반반복 화상 처리가 화상 전체에 화사의 정보와 상관없이 일률적인 방법으로 적용함으로서 생기는 비 효율성을 고려하여 처리하는 화소의 주변 화상 정보를 이용하여 평면 부분과 윤곽 부부느이 처리회수를 달리하여 주므로서 시각적인 효과와 동시에 처리 시간을 단축하는 국부 반복 복원 방법을 제안하였다. 국부 반복 복원 방법은 일반 반복, 복원 알고리즘을 적용하여 윤곽 부분을 집중 복원하고 평면 부분은 복원없이 통과하는 방법으로, 여기에 사용된 일반 반복 알고리즘이 수렴하면 국분 반복 복원도 수렴하게 됨을 이용하였다. 각각 처리된 화상,MSE, 처리 시간등을 비교하여 그 효율성을 확인하였다.

• Journal of Information Processing Systems
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• 제13권6호
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• pp.1628-1639
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• 2017

The combination texture feature extraction approach for texture image retrieval is proposed in this paper. Two kinds of low level texture features were combined in the approach. One of them was extracted from singular value decomposition (SVD) based dual-tree complex wavelet transform (DTCWT) coefficients, and the other one was extracted from multi-scale local binary patterns (LBPs). The fusion features of SVD based multi-directional wavelet features and multi-scale LBP features have short dimensions of feature vector. The comparing experiments are conducted on Brodatz and Vistex datasets. According to the experimental results, the proposed method has a relatively better performance in aspect of retrieval accuracy and time complexity upon the existing methods.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2014년도 춘계학술대회
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• pp.801-803
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• 2014

현대사회에서 영상처리는 여러 분야에서 활용되고 있으며, 이러한 영상처리 중에서 에지 검출은 대부분의 응용에서 필수적이다. 이러한 에지를 검출하기 위한 연구가 국내를 포함한 해외에서 진행되어 오고 있다. 대표적인 에지 검출 방법에는 Sobel, Prewitt, Roberts 등이 있다. 이러한 방법들은 AWGN(additive white Gaussian noise)에 훼손된 영상에서 에지 검출 특성이 미흡하다. 따라서 본 논문에서는 기존의 방법들의 단점을 개선하기 위하여, 국부 마스크를 이용한 에지 검출 방법을 제안하였다.