• 제목/요약/키워드: Infrared Images

검색결과 687건 처리시간 0.034초

다중의 거리영상을 이용한 형태 인식 기법 (Shape-based object recognition using Multiple distance images)

  • 신기선;최해철
    • 대한전자공학회:학술대회논문집
    • /
    • 대한전자공학회 2000년도 추계종합학술대회 논문집(4)
    • /
    • pp.17-20
    • /
    • 2000
  • This paper describes a shape-based object recognition algorithm using multiple distance images. For the images containing dense edge points and noise, previous Hausdorff distance (HD) measures yield a high ms error for object position and many false matchings for recognition. Extended version of HD measure considering edge position and orientation simultaneously is proposed for accurate matching. Multiple distance images are used to calculate proposed matching measure efficiently. Results are presented for visual images and infrared images.

  • PDF

Infrared Scanning Near-Field Optical Microscopy (IR-SNOM) Below the Diffraction Limit

  • Sanghera, J.S.;Aggarwal, I.D.;Cricenti, A.;Generossi, R.;Luce, M.;Perfetti, P.;Margoritondo, G.;Tolk, N.;Piston, D.
    • 세라미스트
    • /
    • 제10권3호
    • /
    • pp.55-66
    • /
    • 2007
  • Infrared Scanning Near-field Optical Microscopy (IR-SNOM) is an extremely powerful analytical instrument since it combines IR spectroscopy's high chemical specificity with SNOM's high spatial resolution. In order to do this in the infrared, specialty chalcogenide glass fibers were fabricated and their ends tapered to generate SNOM probes. The fiber tips were installed in a modified near field microscope and both inorganic and biological samples illuminated with the tunable output from a free-electron laser located at Vanderbilt University. Both topographical and IR spectral images were simultaneously recorded with a resolution of ${\sim}50\;nm$ and ${\sim}100\;nm$, respectively. Unique spectroscopic features were identified in all samples, with spectral images exhibiting resolutions of up to ${\lambda}/60$, or at least 30 times better than the diffraction limited lens-based microscopes. We believe that IR-SNOM can provide a very powerful insight into some of the most important bio-medical research topics.

  • PDF

The horizontal line detection method using Haar-like features and linear regression in infrared images

  • Park, Byoung Sun;Kim, Jae Hyup
    • 한국컴퓨터정보학회논문지
    • /
    • 제20권12호
    • /
    • pp.29-36
    • /
    • 2015
  • In this paper, we propose the horizontal line detection using the Haar-like features and linear regression in infrared images. In the marine environment horizon image is very useful information on a variety of systems. In the proposed method Haar-like features it was noted that the standard deviation be calculated in real time on a static area. Based on the pixel position, calculating the standard deviation of the around area in real time and, if the reaction is to filter out the largest pixel can get the energy map of the area containing the straight horizontal line. In order to select a horizontal line of pixels from the energy map, we applied the linear regression, calculating a linear fit to the transverse horizontal line across the image to select the candidate optimal horizontal. The proposed method was carried out in a horizontal line detecting real infrared image experiment for day and night, it was confirmed the excellent detection results than the legacy methods.

Infrared Target Extraction Using Weighted Information Entropy and Adaptive Opening Filter

  • Bae, Tae Wuk;Kim, Hwi Gang;Kim, Young Choon;Ahn, Sang Ho
    • ETRI Journal
    • /
    • 제37권5호
    • /
    • pp.1023-1031
    • /
    • 2015
  • In infrared (IR) images, near targets have a transient distribution at the boundary region, as opposed to a steady one at the inner region. Based on this fact, this paper proposes a novel IR target extraction method that uses both a weighted information entropy (WIE) and an adaptive opening filter to extract near finely shaped targets in IR images. Firstly, the boundary region of a target is detected using a local variance WIE of an original image. Next, a coarse target region is estimated via a labeling process used on the boundary region of the target. From the estimated coarse target region, a fine target shape is extracted by means of an opening filter having an adaptive structure element. The size of the structure element is decided in accordance with the width information of the target boundary and mean WIE values of windows of varying size. Our experimental results show that the proposed method obtains a better extraction performance than existing algorithms.

웨이블릿 퓨전에 의한 딥러닝 색상화의 성능 향상 (High-performance of Deep learning Colorization With Wavelet fusion)

  • 김영백;최현;조중휘
    • 대한임베디드공학회논문지
    • /
    • 제13권6호
    • /
    • pp.313-319
    • /
    • 2018
  • We propose a post-processing algorithm to improve the quality of the RGB image generated by deep learning based colorization from the gray-scale image of an infrared camera. Wavelet fusion is used to generate a new luminance component of the RGB image luminance component from the deep learning model and the luminance component of the infrared camera. PSNR is increased for all experimental images by applying the proposed algorithm to RGB images generated by two deep learning models of SegNet and DCGAN. For the SegNet model, the average PSNR is improved by 1.3906dB at level 1 of the Haar wavelet method. For the DCGAN model, PSNR is improved 0.0759dB on the average at level 5 of the Daubechies wavelet method. It is also confirmed that the edge components are emphasized by the post-processing and the visibility is improved.

무인기 탑재 열화상(IR) 센서의 농작물 대상 최적 활용 방안 연구 (A Study on the Best Applicationsof Infra-Red(IR) Sensors Mounted on the Unmanned Aerial Vehicles(UAV) in Agricultural Crops Field)

  • 손호웅;김태훈;이희우
    • 한국산업융합학회 논문집
    • /
    • 제26권6_2호
    • /
    • pp.1073-1082
    • /
    • 2023
  • Thermal sensors, also called thermal infrared wavelength sensors, measure temperature based on the intensity of infrared signals that reach the sensor. The infrared signals recognized by the sensor include infrared wavelength(0.7~3.0㎛) and radiant infrared wavelength(3.0~100㎛). Infrared(IR) wavelengths are divided into five bands: near infrared(NIR), shortwave infrared(SWIR), midwave infrared(MWIR), longwave infrared(LWIR), and far infrared(FIR). Most thermal sensors use the LWIR to capture images. Thermal sensors measure the temperature of the target in a non-contact manner, and the data can be affected by the sensor's viewing angle between the target and the sensor, the amount of atmospheric water vapor (humidity), air temperature, and ground conditions. In this study, the characteristics of three thermal imaging sensor models that are widely used for observation using unmanned aerial vehicles were evaluated, and the optimal application field was determined.

영역-점 회귀 크리깅 기반 다중센서 위성영상의 공간-분광 융합: 고해상도 적색 경계 및 단파 적외선 밴드 생성 실험 (Spatio-spectral Fusion of Multi-sensor Satellite Images Based on Area-to-point Regression Kriging: An Experiment on the Generation of High Spatial Resolution Red-edge and Short-wave Infrared Bands)

  • 박소연;강솔아;박노욱
    • 대한원격탐사학회지
    • /
    • 제38권5_1호
    • /
    • pp.523-533
    • /
    • 2022
  • 이 논문에서는 상호보완적인 공간 및 분광해상도를 가진 다중센서 위성영상을 이용하여 공간해상도와 분광해상도를 향상시키기 위해 영역-점 회귀 크리깅(area-to-point regression kriging, ATPRK) 기반의 2단계 spatio-spectral fusion method (2SSFM)을 제안하였다. 2SSFM은 ATPRK와 random forest 회귀 모형을 결합하여 다중센서 위성영상에서 높은 공간해상도를 갖는 분광 밴드를 예측한다. 첫 번째 단계에서는 다중센서 위성영상 사이의 공간해상도 차이를 감소시키기 위해 ATPRK 기반 공간 상세화를 수행한다. 두 번째 단계에서는 다중센서 위성영상 사이의 분광 밴드의 관계성을 정량화하기 위해 random forest를 이용한 회귀 모델링을 적용하였다. 2SSFM의 예측 성능은 적색 경계와 단파 적외선 밴드를 생성하는 사례 연구를 통해 평가하였다. 사례 연구에서 2SSFM은 실제 분광 밴드와 유사한 분광패턴을 보이면서 공간해상도가 향상된 적색 경계와 단파 적외선 밴드를 생성할 수 있었으며, 2SSFM가 고해상도 위성영상에서 제공하지 않은 분광 밴드 생성에 유용함을 확인할 수 있었다. 따라서 2SSFM을 통해 실제로 획득 불가능하지만 환경 모니터링에 효과적인 분광 밴드를 예측함으로써 다양한 분광 지수를 생성할 수 있을 것으로 기대된다.

웨이브렛 변환 영역에서 쿼드트리 기반 적외선 영상 압축 (Quadtree Based Infrared Image Compression in Wavelet Transform Domain)

  • 조창호;이상효
    • 한국통신학회논문지
    • /
    • 제29권3C호
    • /
    • pp.387-397
    • /
    • 2004
  • 영상의 주파수 정보와 공간 정보를 동시에 제공하는 웨이브렛 변환(Wavelet transform)은 영상압축에 매우 효과적임이 밝혀졌고, 최근 들어 웨이브렛 변환 방법으로 다해상도 분해된 영상에 여러 가지 부호화 알고리즘을 적용하는 것에 대해 많은 연구가 진행되고 있다. 본 논문에서는, 웨이브렛 변환으로 다해상도 분해된 적외선 영상에 픽셀간의 상관도와 '0' 정보를 모아 효과적으로 압축할 수 있는 양자화 기법인 쿼드트리 기반 블록 양자화(Quadtree based block quantization)를 적용하여 영상을 압축하는 방법을 제안한파. 웨이브렛 변환된 계수는 스케일간 상잔도가 놀고, 집중도가 높기 때문에 쿼드트리를 적용할 경우 효과적으로 데이터량을 줄일 수 있다. 실험영상으로 256${\times}$256 크기의 8〔bit〕 적외선영상을 이용하고, DCT 압축기법과 제안한 기법을 비교 평가한다.

위성영상을 통한 서울시 지표온도 분석 (The Land Surface Temperature Analysis of Seoul city using Satellite Image)

  • 정종철
    • 환경영향평가
    • /
    • 제22권1호
    • /
    • pp.19-26
    • /
    • 2013
  • The propose of this study is to analyze the optimum spatial resolution of the urban spatial thermal environment structure and to evaluate of the possibility detection using aerial photographs and thermal satellite images. The proper techniques of the optimum spatial resolution for the urban spatial thermal environment structure were analyzed. Thermal infrared satellite image of Seoul city were used for the change rate of surface temperature variation and suggested to the spatial extent and effects of urban surface characteristics and spatial data was interpreted as regions. To extract the surface temperature, Landsat thermal infrared satellite image compared with an automatic weather station data and in the field of the measured temperature and surface temperature by thermal environment affects, the spatial domain has been verified. The surface temperature of the satellite images to extract after adjusting surface temperature isotherms were constructed. The changes in surface temperature from 2008 to 2012 the average surface temperature observation images of changing areas were divided into space. The results of this study are as follows: Through analysis of satellite imagery, Seoul city surface temperature change due to extraction comfort indices were classified into four grades. The comfort index indicative of the temperature of Gangnam-gu, $23.7{\sim}27.2(^{\circ}C)$ range and Songpagu, a $22.7{\sim}30.6(^{\circ}C)$ respectively, the surface temperature of Yeouido $25.8{\sim}32.6(^{\circ}C)$ were in the range.

Effectiveness of Using the TIR Band in Landsat 8 Image Classification

  • Lee, Mi Hee;Lee, Soo Bong;Kim, Yongmin;Sa, Jiwon;Eo, Yang Dam
    • 한국측량학회지
    • /
    • 제33권3호
    • /
    • pp.203-209
    • /
    • 2015
  • This paper discusses the effectiveness of using Landsat 8 TIR (Thermal Infrared) band images to improve the accuracy of landuse/landcover classification of urban areas. According to classification results for the study area using diverse band combinations, the classification accuracy using an image fusion process in which the TIR band is added to the visible and near infrared band was improved by 4.0%, compared to that using a band combination that does not consider the TIR band. For urban area landuse/landcover classification in particular, the producer’s accuracy and user’s accuracy values were improved by 10.2% and 3.8%, respectively. When MLC (Maximum Likelihood Classification), which is commonly applied to remote sensing images, was used, the TIR band images helped obtain a higher discriminant analysis in landuse/landcover classification.