• Journal of Sensor Science and Technology
• /
• v.28 no.3
• /
• pp.152-156
• /
• 2019

An ultraviolet (UV) image sensor is an extremely important optoelectronic device used in scientific and medical applications because it can detect images that cannot be obtained using visible or infrared image sensors. Because photodetectors and transistors are based on different materials, conventional UV imaging devices, which have a hybrid-type structure, require additional complex processes such as a backside etching of a GaN epi-wafer and a wafer-to-wafer bonding for the fabrication of the image sensors. In this study, we developed a monolithic GaN UV passive pixel sensor (PPS) by integrating a GaN-based Schottky-barrier type transistor and a GaN UV photodetector on a wafer. Both individual devices show good electrical and photoresponse characteristics, and the fabricated UV PPS was successfully operated under UV irradiation conditions with a high on/off extinction ratio of as high as $10^3$. This integration technique of a single pixel sensor will be a breakthrough for the development of GaN-based optoelectronic integrated circuits.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.17 no.2
• /
• pp.1-11
• /
• 2021

Salt and pepper is a type of impulse noise. It may appear due to an error in the image transmission process and image storage memory. This noise changes the pixel value at any position in the image to 0 (in case of pepper noise) or 255 (in case of salt noise). In this paper, we present an algorithm for SAP noise reduction. The proposed method consists of three steps. In the first step, the location of the SAP noise is detected, and in the second step, the pixel value of the detected location is restored using a weighted average of the surrounding pixel values. In the last step, a reliability matrix around the reconstructed pixels is constructed, and additional correction is performed with a weighted average using this. As a result of the experiment, the proposed method appears to have similar or higher objective and subjective image quality than previous methods for almost all SAP noise ratios.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.6
• /
• pp.9-18
• /
• 2004

This paper proposes a new and simple stereo matching algorithm using the disparity space image (DSI) technique. First of all, we detect some salient feature points on each scan-line of the image pair and set the matching area using those points and define a simple cost matrix. And we take advantage of matching by pixel-by-pixel instead of using the matching window. While the pixel-by-pixel method boost up the speed of matching, because of no using neighbor information, the correctness of the matching may not be better. To cover this point, we expand the matching path using character of disparity-space-image for using neighbor information. In addition, we devise the compensated matching module using the volume of the disparity space image in order to improve the accuracy of the match. Consequently, we can reduce mismatches at the disparity discontinuities and can obtain the more detailed and correct disparity map.

• Proceedings of the KIEE Conference
• /
• 2007.04a
• /
• pp.26-28
• /
• 2007

The motion estimation is the most important technique in the image compression of the video standards. In the case of next generation standards in the video codec as H.264, a high compression-efficiency can be also obtained by using a motion compensation. To obtain the accurate motion search, a motion estimation should be achieved up to 1/2 pixel and 1/4 pixel uiuts. To do this, the computational complexity is increased although the image compression rate is increased. Therefore, in this paper, we propose the advanced sub-pixel block matching algorithm to reduce the computational complexity by using a statistical characteristics of SAD(Sum of Absolute Difference). Generally, the probability of the minimum SAD values is high when searching point is in the distance 1 from the reference point. Thus, we reduced the searching area and then we can overcome the computational complexity problem. The main concept of proposed algorithm, which based on TSS(Three Step Search) method, first we find three minimum SAD points which is in integer distance unit, and then, in second step, the optimal point is in 1/2 pixel unit either between the most minimum SAD value point and the second minimum SAD point or between the most minimum SAD value point and the third minimum SAD point In third step, after finding the smallest SAD value between two SAD values on 1/2 pixel unit, the final optimized point is between the most minimum SAD value and the result value of the third step, in 1/2 pixel unit i.e., 1/4 pixel unit in totally. The conventional TSS method needs an eight.. search points in the sub-pixel steps in 1/2 pixel unit and also an eight search points in 1/4 pixel, to detect the optimal point. However, in proposed algorithm, only total five search points are needed. In the result. 23 % improvement of processing speed is obtained.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.359-362
• /
• 2004

In multi-dimensional image, ICA-based feature extraction algorithm, which is proposed in this paper, is for the purpose of detecting target feature about pixel assumed as a linear mixed spectrum sphere, which is consisted of each different type of material object (target feature and background feature) in spectrum sphere of reflectance of each pixel. Landsat ETM+ satellite image is consisted of multi-dimensional data structure and, there is target feature, which is purposed to extract and various background image is mixed. In this paper, in order to eliminate background features (tidal flat, seawater and etc) around target feature (laver farm) effectively, pixel spectrum sphere of target feature is projected onto the orthogonal spectrum sphere of background feature. The rest amount of spectrum sphere of target feature in the pixel can be presumed to remove spectrum sphere of background feature. In order to make sure the excellence of feature extraction method based on ICA, which is proposed in this paper, laver farm feature extraction from Landsat ETM+ satellite image is applied. Also, In the side of feature extraction accuracy and the noise level, which is still remaining not to remove after feature extraction, we have conducted a comparing test with traditionally most popular method, maximum-likelihood. As a consequence, the proposed method from this paper can effectively eliminate background features around mixed spectrum sphere to extract target feature. So, we found that it had excellent detection efficiency.

• The Journal of the Korea Contents Association
• /
• v.16 no.7
• /
• pp.431-438
• /
• 2016

In this paper, we present an upsampling technique for depth map image using color and depth weights. First, we construct a high-resolution image using the bilinear interpolation technique. Next, we detect a common edge region using RGB color space, HSV color space, and depth image. If an interpolated pixel belongs to the common edge region, we calculate weighting values of color and depth in $3{\times}3$ neighboring pixels and compute the cost value to determine the boundary pixel value. Finally, the pixel value having minimum cost is determined as the pixel value of the high-resolution depth image. Simulation results show that the proposed algorithm achieves good performance in terns of PSNR comparison and subjective visual quality.

• Korean Journal of Remote Sensing
• /
• v.33 no.6_1
• /
• pp.1003-1017
• /
• 2017

Multispectral image data of high spatial resolution is required to obtain correct information on the ground surface. The multispectral image data has lower resolution compared to panchromatic data. PAN-sharpening fusion technique produces the multispectral data with higher resolution of panchromatic image. Recently the object-based approach is more applied to the high spatial resolution data than the conventional pixel-based one. For the object-based image analysis, it is necessary to perform image segmentation that produces the objects of pixel group. Image segmentation can be effectively achieved by the process merging step-by-step two neighboring regions in RAG (Regional Adjacency Graph). In the satellite remote sensing, the operational environment of the satellite sensor causes image degradation during the image acquisition. This degradation increases variation of pixel values in same area, and results in deteriorating the accuracy of image segmentation. An iterative approach that reduces the difference of pixel values in two neighboring pixels of same area is employed to alleviate variation of pixel values in same area. The size of segmented regions is associated with the quality of image segmentation and is decided by a stopping rue in the merging process. In this study, the image restoration and segmentation was quantitatively evaluated using simulation data and was also applied to the three PAN-sharpened multispectral images of high resolution: Dubaisat-2 data of 1m panchromatic resolution from LA, USA and KOMPSAT3 data of 0.7m panchromatic resolution from Daejeon and Chungcheongnam-do in the Korean peninsula. The experimental results imply that the proposed method can improve analytical accuracy in the application of remote sensing high resolution PAN-sharpened multispectral imagery.

• 전기의세계
• /
• v.30 no.12
• /
• pp.793-796
• /
• 1981

최근 우리나라에도 digital image processing에 대한 연구가 활발이 진행되고 있다. 또한 digital image processing의 생체공학에의 응용도 괄목할 만하다. 이러한 연구와 응용에 도움이 되고자 microcomputer를 이용한 image processor설계의 실례를 기술하고자 한다. 이 설계는 목적 image를 stationary image로 가정하여 TV카메라의 영상신호를 sample하여 computer 기억장치에 저장하므로 가격이 저렴하게 된다. 이러한 장치로서는 DMA연결 (Direct Memory Access interface)을 사용하여 빠른 data transfer를 달성할 수 있다. Digital image processing계는 기본적으로 microcomputer가 TV카메라와 TV모니터에 연결된 구조를 하고 있다. Computer가 기억장치에 저장된 data를 처리하여 필요한 정보를 얻게 된다. 이러한 data 처리를 하므로서 image를 사용자가 해석하기 쉽도록 image질을 향상시키거나 computer가 image를 인식하게 한다. 이와같이 처리된 image는 TV모니터를 통해서 볼 수 있다. 본지에서는 256x256개의 pixel들로 이루어지고, 각개의 pixel은 4개의 bit로 구성된 image processor의 설계를 기술한다.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.28B no.7
• /
• pp.566-577
• /
• 1991

In this paper, the method of image segmentation based on a pyramid of reduced resolution versions of the input input image is persented. In a pyramid structure, two regions (a given pixel and its mother pixels) are compared by the proposed inverse-mother-son variance ratio (IMSVR) method for the detection of an optinal object pixel and are determined whether they are similar enough to be viewed as one region or disparate to be viewed as ditinct regions By the proposed method, an l`timal object pixel has been setectedat some level, it is necessary to retrieve its boundary precisely. Moving down the pyramid to levels of higher resolution is requires. In this paper, the top-sown pyramid traversing algorithm for an image segmentation using a pyrmid structure is presented. Using the computer simulation, the results by the proposed statistical method and object traversing method are investigated for the binary image and the real image at the results of computer simulation, the proposed method of image segmentation based on a pyramid structure seem to have useful properties and deserve consideration as a possible alternative to existing methods of omage segmentation. The computation for the proposed method is required 0 (log n), for an TEX>$n{\times}n$ input image.

• Journal of the Korea Society of Computer and Information
• /
• v.23 no.4
• /
• pp.147-153
• /
• 2018

In this paper, we propose an efficient WBC 14-Diff classification which performs using the WBC-ResNet-152, a type of CNN model. The main point of view is to use Super-pixel for the segmentation of the image of WBC, and to use ResNet for the classification of WBC. A total of 136,164 blood image samples (224x224) were grouped for image segmentation, training, training verification, and final test performance analysis. Image segmentation using super-pixels have different number of images for each classes, so weighted average was applied and therefore image segmentation error was low at 7.23%. Using the training data-set for training 50 times, and using soft-max classifier, TPR average of 80.3% for the training set of 8,827 images was achieved. Based on this, using verification data-set of 21,437 images, 14-Diff classification TPR average of normal WBCs were at 93.4% and TPR average of abnormal WBCs were at 83.3%. The result and methodology of this research demonstrates the usefulness of artificial intelligence technology in the blood cell image classification field. WBC-ResNet-152 based morphology approach is shown to be meaningful and worthwhile method. And based on stored medical data, in-depth diagnosis and early detection of curable diseases is expected to improve the quality of treatment.