• 한국정보전자통신기술학회논문지
• /
• 제4권3호
• /
• pp.174-181
• /
• 2011

본 논문에서는 적외선 위성영상과 광학 위성영상을 위한 정합방법을 제안하였다. 적외선 영상은 물체에서 방사하는 열에너지를 측정한 것으로, 광학 영상과는 다른 정보를 보여주는 장점으로 많은 분야에 응용된다. 하지만 적외선 영상은 대비가 광학 영상에 비해 낮아, 영상 정합을 위한 특징점 추출 및 매칭을 하기가 어렵다. 이를 극복하기 위해, Modifed SIFT(Scale Invariant Feature Transform)를 사용하여 특징점을 추출 및 매칭하였다. 또한 특징점의 상대적 변별력을 증가시키기 위해, 영상을 블록화해서 Modified SIFT와 RANSAC (RANdom SAample Concensus)을 적용하였다. 마지막으로 오매칭이 있는 블록의 특징점을 제거하기 위해, 각 블록에서 추출된 특징점을 원 영상의 좌표계로 통합해 RANSAC을 다시 한 번 적용하였다. 실험에 사용된 적외선 영상의 파장대역은 3~5um이며, 실험결과 제안된 방법은 적외선과 광학 영상정합에 강인한 성능을 보였다.

• 한국군사과학기술학회지
• /
• 제12권4호
• /
• pp.500-507
• /
• 2009

This paper presents a novel method which can detect a target in IR image for active protection system. The target in IR image for the active protection system is small, moreover it moves with enormous speed. The proposed algorithm is comprised of robust clutter rejection methods and target optimized detection algorithms for small target, and an advanced method of selecting a final target position in target area, it can work in some milliseconds. The proposed algorithm provides the active protective system with more correct positions than those of radar, so that helps the active protection system can defense all threats with the utmost precision.

• 한국군사과학기술학회지
• /
• 제22권2호
• /
• pp.162-169
• /
• 2019

This paper describes a thermal image processing algorithm for uncooled type TEC-less IR detector which is applicable to fire control system of small arms. We implemented a real-time gain and offset compensation algorithm based on polynomial approximation from the raw dataset which is acquired by two reference temperature of blackbody from various FPA(Focal Plane Array) temperature. Through the experiment, we analyzed the output characteristics of detector's raw-data and compared IR image quality to traditional non-uniformity correction method. It shows that the proposed method works well in all FPA temperature range with low residual non-uniformity.

• 한국컴퓨터정보학회논문지
• /
• 제23권1호
• /
• pp.33-39
• /
• 2018

In this paper, We studied the possibility of SoC(System On Chip) design using infrared image processing IP(Intellectual Property). And, we studied NUC(Non Uniformity Correction), BPR(Bad Pixel Recovery), and CEM(Contrast Enhancement) processing, the infrared image processing algorithm implemented by IP. We showed the logic and timing diagram implemented through the hardware block designed based on each algorithm. Each algorithm was coded as RTL(Register Transfer Level) using Verilog HDL(Hardware Description Language), ALTERA QUARTUS synthesis, and programed in FPGA(Field Programmable Gated Array). In addition, we have verified that the image data is processed at each algorithm without any problems by integrating the infrared image processing algorithm. Particularly, using the directly manufactured electronic board, Processor, SRAM, and FLASH are interconnected and tested and the verification result is presented so that the SoC type can be realized later. The infrared image processing IP proposed and verified in this study is expected to be of high value in the future SoC semiconductor fabrication. In addition, we have laid the basis for future application in the camera SoC industry.

• 대한원격탐사학회지
• /
• 제36권4호
• /
• pp.545-555
• /
• 2020

This paper focuses on automatic image registration between EO (Electro-Optical) and IR (InfraRed) satellite images with different spectral properties using block-based approach and simple preprocessing technique to enhance the performance of feature matching. If unpreprocessed EO and IR images from Kompsat-3A satellite were applied to local feature matching algorithms(Scale Invariant Feature Transform, Speed-Up Robust Feature, etc.), image registration algorithm generally failed because of few detected feature points or mismatched pairs despite of many detected feature points. In this paper, we proposed a new image registration method which improved the performance of feature matching with block-based registration process on 9-divided image and pre-processing technique based on adaptive histogram equalization. The proposed method showed better performance than without our proposed technique on visual inspection and I-RMSE. This study can be used for automatic image registration between various images acquired from different sensors.

• Journal of Astronomy and Space Sciences
• /
• 제27권4호
• /
• pp.309-318
• /
• 2010

We introduce a technical approach for reducing three-dimensional infrared (IR) spectroscopic data generated by integral field spectroscopy or slit-scanning observations. The first part of data reduction using IRAF presents a guideline for processing spectral images from long-slit IR spectroscopy. Multichannel image reconstruction, Image Analysis and Display (MIRIAD) is used in the later part to construct and analyze the data cubes which contain spatial and kinematic information of the objects. This technic has been applied to a sample data set of diffuse 2.1218 ${\mu}m$ $H_2$ 1-0 S(1) emission features observed by slit-scanning around Sgr A East in the Galactic center. Details of image processing for the high-dispersion infrared data are described to suggest a sequence of contamination cleaning and distortion correction. Practical solutions for handling data cubes are presented for survey observations with various configurations of slit positioning.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
• /
• pp.282-285
• /
• 2006

This paper analyzed the characteristics of the Lossy JPEG of the meteorological satellite image, and analyzed the quality of the Lossy JPEG compression, which is proper for the LRIT(Low Rate Information Transmission) to be serviced to the SDUS(Small-scale Data Utilization Station) system of the COMS(Communication, Oceans, Meteorological Satellite). Since COMS is to start running after 2008, we collected the data of the MTSAT-1R(Multi-functional Transport Satellite -1R) for analysis, and after forming the original image to be used to LRIT by each channel and time zone of the satellite image data, we set the different quality with the Lossy JPEG compression, and compressed the original data. For the characteristic analysis of the Lossy JPEG, we measured PSNR(Peak Signal to Noise Rate), compression rate and the time spent in compression following each quality of Lossy JPEG compression. As a result of the analysis of the satellite image data of the MTSAT-1R, the ideal quality of the Lossy JPEG compression was found to be 90% in the VIS Channel, 85% in the IR1 Channel, 80% in the IR2 Channel, 90% in the IR3 Channel and 90% in the IR4 Channel.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제16권4호
• /
• pp.246-253
• /
• 2016

Infrared (IR) imaging has been researched for various applications such as surveillance. IR radiation has the capability to detect thermal characteristics of objects under low-light conditions. However, automatic segmentation for finding the object of interest would be challenging since the IR detector often provides the low spatial and contrast resolution image without color and texture information. Another hindrance is that the image can be degraded by noise and clutters. This paper proposes multi-level segmentation for extracting regions of interest (ROIs) and objects of interest (OOIs) in the IR scene. Each level of the multi-level segmentation is composed of a k-means clustering algorithm, an expectation-maximization (EM) algorithm, and a decision process. The k-means clustering initializes the parameters of the Gaussian mixture model (GMM), and the EM algorithm estimates those parameters iteratively. During the multi-level segmentation, the area extracted at one level becomes the input to the next level segmentation. Thus, the segmentation is consecutively performed narrowing the area to be processed. The foreground objects are individually extracted from the final ROI windows. In the experiments, the effectiveness of the proposed method is demonstrated using several IR images, in which human subjects are captured at a long distance. The average probability of error is shown to be lower than that obtained from other conventional methods such as Gonzalez, Otsu, k-means, and EM methods.

• Journal of Radiation Protection and Research
• /
• 제35권1호
• /
• pp.26-33
• /
• 2010

비파괴검사 분야의 방사선 검사(RT) 방식은 image plate (IP)를 사용한 Computed Radiography(CR) 영상시스템의 도입에 따라 필름 방식의 아날로그 영상이 점차 디지털 영상으로 교체되고 있다. 비파괴검사에서 결함을 효과적으로 검출할 수 있는 영상의 품질은 촬영 조건, 영상획득매체, 사용 선원의 종류 및 촬영 거리, 검사체 두께등이 영향을 미친다. 본 논문에서는 비파괴 검사 분야에 적용할 수 있는 감마선원의 기본 특성을 조사하였고, FUJI사에서 개발한 CR 영상 시스템에 $^{75}Se$, $^{192}Ir$ 동위원소를 적용하여 영상을 획득하였다. 획득된 영상의 gray scale을 이미지 소프트웨어를 통해 추출한 후에 대조도 및 신호대잡음비를 계산하고 비교 분석하였다. 또한 투과도계를 이용한 비교 영상을 통하여 식별도를 분석하였다.

• 전자공학회논문지
• /
• 제53권11호
• /
• pp.73-81
• /
• 2016

일반적으로 적외선 열화상 영상은 가시광선 영상보다 약한 선명도를 가지며, 디테일 정보도 거의 없다. 그래서 종래 영상확대 알고리즘 방법으로 적외선 영상을 확대할 경우 가시광 영상에 비해 효과적이지 않다. 이런 문제점을 해결하기 위해 본 논문은 입력 적외선 영상을 ADRC 기반 초고해상도 기법으로 일차적으로 확대하고, 대응하는 가시광선 영상과 융합하는 방법을 제안한다. 제안하는 알고리즘은 크게 확대 과정과 융합 과정으로 나뉜다. 먼저 입력된 적외선 영상을 ADRC 기반의 초고해상도 알고리즘으로 확대한다. 사전의 학습과정에서 고해상도 영상들에 소위 pre-emphasis를 적용한 후 학습을 함으로써 선명도 향상을 꾀했다. 융합 과정에서는 먼저 입력 IR영상과 대응하는 가시광선 영상에서 고주파 정보를 추출하고, IR영상의 복잡도에 따라 적응적으로 상기 추출된 고주파 정보를 합성하는 방식으로 최종적인 확대 적외선 영상이 얻어진다. 모의 실험 결과 제안 알고리즘은 최신 SR기법 중 하나인 A+기법보다 JNB수치가 평균 0.2184만큼 높은 우수한 정량적 결과를 보인다. 뿐만 아니라 주관적 화질에서도 상당한 우위를 보인다.