• Title, Summary, Keyword: Spatial resolution

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Characteristics of Multi-Spatial Resolution Satellite Images for the Extraction of Urban Environmental Information

  • Seo, Dong-Jo;Park, Chong-Hwa;Tateishi, Ryutaro
    • Proceedings of the KSRS Conference
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    • pp.218-224
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    • 1998
  • The coefficients of variation obtained from three typical vegetation indices of eight levels of multi-spatial resolution images in urban areas were employed to identify the optimum spatial resolution in terms of maintaining information quality. These multi-spatial resolution images were prepared by degrading 1 meter simulated, 16 meter ADEOS/AVNIR, and 30 meter Landsat-TM images. Normalized Difference Vegetation Index (NDVI), Perpendicular Vegetation Index (PVI) and Soil Adjusted Ratio Vegetation Index (SARVI) were applied to reduce data redundancy and compare the characteristics of multi-spatial resolution image of vegetation indices. The threshold point on the curve of the coefficient of variation was defined as the optimum resolution level for the analysis with multi-spatial resolution image sets. Also, the results from the image segmentation approach of region growing to extract man-made features were compared with these multi-spatial resolution image sets.

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Neighborhood Correlation Image Analysis for Change Detection Using Different Spatial Resolution Imagery

  • Im, Jung-Ho
    • Korean Journal of Remote Sensing
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    • v.22 no.5
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    • pp.337-350
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    • 2006
  • The characteristics of neighborhood correlation images for change detection were explored at different spatial resolution scales. Bi-temporal QuickBird datasets of Las Vegas, NV were used for the high spatial resolution image analysis, while bi-temporal Landsat $TM/ETM^{+}$ datasets of Suwon, South Korea were used for the mid spatial resolution analysis. The neighborhood correlation images consisting of three variables (correlation, slope, and intercept) were evaluated and compared between the two scales for change detection. The neighborhood correlation images created using the Landsat datasets resulted in somewhat different patterns from those using the QuickBird high spatial resolution imagery due to several reasons such as the impact of mixed pixels. Then, automated binary change detection was also performed using the single and multiple neighborhood correlation image variables for both spatial resolution image scales.

Increasing Spatial Resolution of Remotely Sensed Image using HNN Super-resolution Mapping Combined with a Forward Model

  • Minh, Nguyen Quang;Huong, Nguyen Thi Thu
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.31 no.6_2
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    • pp.559-565
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    • 2013
  • Spatial resolution of land covers from remotely sensed images can be increased using super-resolution mapping techniques for soft-classified land cover proportions. A further development of super-resolution mapping technique is downscaling the original remotely sensed image using super-resolution mapping techniques with a forward model. In this paper, the model for increasing spatial resolution of remote sensing multispectral image is tested with real SPOT 5 imagery at 10m spatial resolution for an area in Bac Giang Province, Vietnam in order to evaluate the feasibility of application of this model to the real imagery. The soft-classified land cover proportions obtained using a fuzzy c-means classification are then used as input data for a Hopfield neural network (HNN) to predict the multispectral images at sub-pixel spatial resolution. The 10m SPOT multispectral image was improved to 5m, 3,3m and 2.5m and compared with SPOT Panchromatic image at 2.5m resolution for assessment.Visually, the resulted image is compared with a SPOT 5 panchromatic image acquired at the same time with the multispectral data. The predicted image is apparently sharper than the original coarse spatial resolution image.

Detector Motion Method to Increase Spatial Resolution in Photon-Counting Detectors

  • Lee, Daehee;Park, Kyeongjin;Lim, Kyung Taek;Cho, Gyuseong
    • Journal of the Korean Physical Society
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    • v.70 no.6
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    • pp.567-573
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    • 2017
  • Medical imaging requires high spatial resolution of an image to identify fine lesions. Photon-counting detectors in medical imaging have recently been rapidly replacing energy-integrating detectors due to the former's high spatial resolution, high efficiency and low noise. Spatial resolution in a photon counting image is determined by the pixel size. Therefore, the smaller the pixel size, the higher the spatial resolution that can be obtained in an image. However, detector redesigning is required to reduce pixel size, and an expensive fine process is required to integrate a signal processing unit with reduced pixel size. Furthermore, as the pixel size decreases, charge sharing severely deteriorates spatial resolution. To increase spatial resolution, we propose a detector motion method using a large pixel detector that is less affected by charge sharing. To verify the proposed method, we utilized a UNO-XRI photon-counting detector (1-mm CdTe, Timepix chip) at the maximum X-ray tube voltage of 80 kVp. A similar spatial resolution of a $55-{\mu}m-pixel$ image was achieved by application of the proposed method to a $110-{\mu}m-pixel$ detector with a higher signal-to-noise ratio. The proposed method could be a way to increase spatial resolution without a pixel redesign when pixels severely suffer from charge sharing as pixel size is reduced.

Analysis of Spatial Structure in Geographic Data with Changing Spatial Resolution (해상도 변화에 따른 공간 데이터의 구조특성 분석)

  • 구자용
    • Spatial Information Research
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    • v.8 no.2
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    • pp.243-255
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    • 2000
  • The spatial distribution characteristics and patterns of geographic features in space can be understood through a variety of analysis techniques. The scale is one of most important factors in spatial analysis techniques. This study is aimed at identifying the characteristics of spatial data with a coarser spatial resolution and finding procedures for spatial resolution in operational scale. To achieve these objectives, this study selected LANSAT TM imagery for Sunchon Bay, a coastal wetland for a study site, applied the indices for representing scale characteristics with resolution, and compared those indices. Local variance and fractal dimension developed by previous studies were applied to measure the textual characteristics. In this study, Moran s I was applied to measure spatial pattern change of variance data which were generated from the process of coarser resolution. Drawing upon the Moran s I of variancedata was optimum technique for analysing spatial structure than those of previous studies (local variance and fractal dimension). When the variance data represents maximum Moran´s I at certainly resolution, spatial data reveals maximum change at that resolution. The optimum resolution for spatial data can be explored by applying these results.

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Resolution of Temporal-Multiplexing and Spatial-Multiplexing Stereoscopic Televisions

  • Kim, Joohwan;Banks, Martin S.
    • Current Optics and Photonics
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    • v.1 no.1
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    • pp.34-44
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    • 2017
  • Stereoscopic (S3D) displays present different images to the two eyes. Temporal multiplexing and spatial multiplexing are two common techniques for accomplishing this. We compared the effective resolution provided by these two techniques. In a psychophysical experiment, we measured resolution at various viewing distances on a display employing temporal multiplexing, and on another display employing spatial multiplexing. In another experiment, we simulated the two multiplexing techniques on one display and again measured resolution. The results show that temporal multiplexing provides greater effective resolution than spatial multiplexing at short and medium viewing distances, and that the two techniques provide similar resolution at long viewing distance. Importantly, we observed a significant difference in resolution at the viewing distance that is generally recommended for high-definition television.

Measurement of Spatial Resolution in Fiber-optic Image Guides

  • Lee, Bong-Soo
    • Journal of the Optical Society of Korea
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    • v.5 no.2
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    • pp.33-36
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    • 2001
  • Common methods of determining the spatial resolution of fiber-optic image guides are by measuring the diameter of individual microfibers or by the use of a resolution test target. However these methods cannot provide enough information of spatial resolution in ultrathin fiber-optic image guides. In this study, a simple method to measure the modulation transfer function (MTF) of an mage guide was developed. The MTFs of ultrathin image guides with 3 and 4${\mu}{\textrm}{m}$ Um diameter were measured by examining transmitted sharp edge image. This method should be especially useful for measuring spatial resolution of ultrahigh resolution image guides with less than 5 ${\mu}{\textrm}{m}$ diameter microfibers because their spatial resolution cannot be determined by individual microfiber diameter due to crosstalk and leaky ray phenomena.

Land Cover Super-resolution Mapping using Hopfield Neural Network for Simulated SPOT Image

  • Nguyen, Quang Minh
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.6_2
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    • pp.653-663
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    • 2012
  • Using soft classification, it is possible to obtain the land cover proportions from the remotely sensed image. These land cover proportions are then used as input data for a procedure called "super-resolution mapping" to produce the predicted hard land cover layers at higher resolution than the original remotely sensed image. Superresolution mapping can be implemented using a number of algorithms in which the Hopfield Neural Network (HNN) has showed some advantages. The HNN has improved the land cover classification through superresolution mapping greatly with the high resolution data. However, the super-resolution mapping is based on the spatial dependence assumption, therefore it is predicted that the accuracy of resulted land cover classes depends on the relative size of spatial features and the spatial resolution of the remotely sensed image. This research is to evaluate the capability of HNN to implement the super-resolution mapping for SPOT image to create higher resolution land cover classes with different zoom factor.

Assessment of the Ochang Plain NDVI using Improved Resolution Method from MODIS Images (MODIS영상의 고해상도화 수법을 이용한 오창평야 NDVI의 평가)

  • Park, Jong-Hwa;La, Sang-Il
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.9 no.6
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    • pp.1-12
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    • 2006
  • Remote sensing cannot provide a direct measurement of vegetation index (VI) but it can provide a reasonably good estimate of vegetation index, defined as the ratio of satellite bands. The monitoring of vegetation in nearby urban regions is made difficult by the low spatial resolution and temporal resolution image captures. In this study, enhancing spatial resolution method is adapted as to improve a low spatial resolution. Recent studies have successfully estimated normalized difference vegetation index (NDVI) using improved resolution method such as from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard EOS Terra satellite. Image enhancing spatial resolution is an important tool in remote sensing, as many Earth observation satellites provide both high-resolution and low-resolution multi-spectral images. Examples of enhancement of a MODIS multi-spectral image and a MODIS NDVI image of Cheongju using a Landsat TM high-resolution multi-spectral image are presented. The results are compared with that of the IHS technique is presented for enhancing spatial resolution of multi-spectral bands using a higher resolution data set. To provide a continuous monitoring capability for NDVI, in situ measurements of NDVI from paddy field was carried out in 2004 for comparison with remotely sensed MODIS data. We compare and discuss NDVI estimates from MODIS sensors and in-situ spectroradiometer data over Ochang plain region. These results indicate that the MODIS NDVI is underestimated by approximately 50%.

Image Fusion Framework for Enhancing Spatial Resolution of Satellite Image using Structure-Texture Decomposition (구조-텍스처 분할을 이용한 위성영상 융합 프레임워크)

  • Yoo, Daehoon
    • Journal of the Korea Computer Graphics Society
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    • v.25 no.3
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    • pp.21-29
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    • 2019
  • This paper proposes a novel framework for image fusion of satellite imagery to enhance spatial resolution of the image via structure-texture decomposition. The resolution of the satellite imagery depends on the sensors, for example, panchromatic images have high spatial resolution but only a single gray band whereas multi-spectral images have low spatial resolution but multiple bands. To enhance the spatial resolution of low-resolution images, such as multi-spectral or infrared images, the proposed framework combines the structures from the low-resolution image and the textures from the high-resolution image. To improve the spatial quality of structural edges, the structure image from the low-resolution image is guided filtered with the structure image from the high-resolution image as the guidance image. The combination step is performed by pixel-wise addition of the filtered structure image and the texture image. Quantitative and qualitative evaluation demonstrate the proposed method preserves spectral and spatial fidelity of input images.