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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Atmospheric correction of remotely sensed image data by a simplified model

The interaction of radiation with the atmosphere is complex and has proved difficult to calculate without reference to measurements made at or close to the time and location of interest. In this paper we describe the use of data from an airborne-tracking sunphotometer mounted on a NASA C-130 aircraft to derive optical properties of the atmospheric aerosols above the aircraft when it is on the ground as well as when the aircraft is at altitude collecting remote sensing data. Furthermore, we describe the use of these optical properties for quantitative atmospheric correction of Landsat Thematic Mapper (TM) and NS001 TM simulator radiances in a simplified radiative transfer model appropriate for each pixel of entire images. Both qualitative and quantitative comparisons of results from use of the model show it provides good to excellent correction for atmospheric effects in TM and NS001 TM simulator data. Quantitative comparisons with measurements of surface radiances measured near the time of the TM overpass showed agreement within a few percent for bands 2, 3, and 4. Band 1 yielded radiances within 15 percent of the surface radiances. We think the simplified atmospheric correction model shows great promise for applying atmospheric corrections to entire images instead of individual points within images to yield surface radiances within a few percent in a computationally efficient manner.

Wrigley, R. C.↗
NASA NTRS1974

Preparation of remotely-sensed image data for land use planning

Preliminary processing operations required before computer compatible tapes (CCT) can be utilized routinely to realize the full potential of ERTS imagery for rapid mensuration, quantitative estimation and for detecting and monitoring changes over time are described. Geographic referencing, geometric manipulations, classification, and association overlays (as of political boundaries) are discussed.

Bond, A. D.↗
NASA NTRS1984

An application of expert systems technology to remotely sensed image analysis

In October of 1983, a project was initiated at NASA/Ames Research Center to design a prototype expert system capable of producing a preliminary land cover classification from an unsupervised classification of Landsat Multispectral Scanner (MSS) imagery and associated collateral data. This paper outlines the problem of determining land cover classes from an unsupervised classification, presents a brief overview of expert systems, and continues with a description of the design and current state of implementation of NASA/Ames' prototype Landsat MSS image analysis expert system.

Erickson, W. K.↗
NASA NTRS1990

Applications of high-resolution remote sensing image data

There are many situations in which the image resolution of satellite data is insufficient to provide the detail required for resource management and environmental monitoring. This paper will focus on applications of high-resolution (0.4 to 10 m) airborne multispectral and imaging spectrometer data acquired in Canada using the MEIS II multispectral line imager and the PMI imaging spectrometer. Applications discussed will include forestry, mapping, and geobotany.

Strome, W. M.↗
NASA NTRS1993

An investigative study of multispectral data compression for remotely-sensed images using vector quantization and difference-mapped shift-coding

A study is conducted to investigate the effects and advantages of data compression techniques on multispectral imagery data acquired by NASA's airborne scanners at the Stennis Space Center. The first technique used was vector quantization. The vector is defined in the multispectral imagery context as an array of pixels from the same location from each channel. The error obtained in substituting the reconstructed images for the original set is compared for different compression ratios. Also, the eigenvalues of the covariance matrix obtained from the reconstructed data set are compared with the eigenvalues of the original set. The effects of varying the size of the vector codebook on the quality of the compression and on subsequent classification are also presented. The output data from the Vector Quantization algorithm was further compressed by a lossless technique called Difference-mapped Shift-extended Huffman coding. The overall compression for 7 channels of data acquired by the Calibrated Airborne Multispectral Scanner (CAMS), with an RMS error of 15.8 pixels was 195:1 (0.41 bpp) and with an RMS error of 3.6 pixels was 18:1 (.447 bpp). The algorithms were implemented in software and interfaced with the help of dedicated image processing boards to an 80386 PC compatible computer. Modules were developed for the task of image compression and image analysis. Also, supporting software to perform image processing for visual display and interpretation of the compressed/classified images was developed.

Jaggi, S.↗
NASA NTRS1995

Remotely sensed image compression based on wavelet transform

In this paper, we present an image compression algorithm that is capable of significantly reducing the vast amount of information contained in multispectral images. The developed algorithm exploits the spectral and spatial correlations found in multispectral images. The scheme encodes the difference between images after contrast/brightness equalization to remove the spectral redundancy, and utilizes a two-dimensional wavelet transform to remove the spatial redundancy. the transformed images are then encoded by Hilbert-curve scanning and run-length-encoding, followed by Huffman coding. We also present the performance of the proposed algorithm with the LANDSAT MultiSpectral Scanner data. The loss of information is evaluated by PSNR (peak signal to noise ratio) and classification capability.

Kim, Seong W.↗
NASA NTRS2005

Monitoring Change Through Hierarchical Segmentation of Remotely Sensed Image Data

NASA's Goddard Space Flight Center has developed a fast and effective method for generating image segmentation hierarchies. These segmentation hierarchies organize image data in a manner that makes their information content more accessible for analysis. Image segmentation enables analysis through the examination of image regions rather than individual image pixels. In addition, the segmentation hierarchy provides additional analysis clues through the tracing of the behavior of image region characteristics at several levels of segmentation detail. The potential for extracting the information content from imagery data based on segmentation hierarchies has not been fully explored for the benefit of the Earth and space science communities. This paper explores the potential of exploiting these segmentation hierarchies for the analysis of multi-date data sets, and for the particular application of change monitoring.

Tilton, James C.↗
NASA NTRS2006

Utilizing Hierarchical Segmentation to Generate Water and Snow Masks to Facilitate Monitoring Change with Remotely Sensed Image Data

The hierarchical segmentation (HSEG) algorithm is a hybrid of hierarchical step-wise optimization and constrained spectral clustering that produces a hierarchical set of image segmentations. This segmentation hierarchy organizes image data in a manner that makes the image's information content more accessible for analysis by enabling region-based analysis. This paper discusses data analysis with HSEG and describes several measures of region characteristics that may be useful analyzing segmentation hierarchies for various applications. Segmentation hierarchy analysis for generating landwater and snow/ice masks from MODIS (Moderate Resolution Imaging Spectroradiometer) data was demonstrated and compared with the corresponding MODIS standard products. The masks based on HSEG segmentation hierarchies compare very favorably to the MODIS standard products. Further, the HSEG based landwater mask was specifically tailored to the MODIS data and the HSEG snow/ice mask did not require the setting of a critical threshold as required in the production of the corresponding MODIS standard product.

Tilton, James C.↗
NASA NTRS2017

Method and System for Physiologically Modulating Videogames and Simulations which Use Gesture and Body Image Sensing Control Input Devices

Method for physiologically modulating videogames and simulations includes utilizing input from a motion-sensing video game system and input from a physiological signal acquisition device. The inputs from the physiological signal sensors are utilized to change the response of a user's avatar to inputs from the motion-sensing sensors. The motion-sensing system comprises a 3D sensor system having full-body 3D motion capture of a user's body. This arrangement encourages health-enhancing physiological self-regulation skills or therapeutic amplification of healthful physiological characteristics. The system provides increased motivation for users to utilize biofeedback as may be desired for treatment of various conditions.

Pope, Alan T.↗
NASA NTRS2017

Registration of Textured Remote Sensing Images Using Directional Gabor Frames

In this paper we propose to utilize a new concept of discrete directional Gabor frames for automatic image registration. The directional Gabor representations have been shown to provide more accurate feature extraction than directional wavelet transforms for images where texture is the dominant feature. Initial experimental results are presented here which indicate that discrete directional Gabor frames exhibit strong correlations, which indicates that they are likely to improve the existing image registration toolbox.

Image Processing; Pattern Recognition↗
NASA NTRS2017

Registration of Textured Remote Sensing Images Using Directional Gabor Frames

In this paper we propose to utilize a new concept of discrete directional Gabor frames for automatic image registration. The directional Gabor representations have been shown to provide more accurate feature extraction than directional wavelet transforms for images where texture is the dominant feature. Initial experimental results are presented here which indicate that discrete directional Gabor frames exhibit strong correlations, which indicates that they are likely to improve the existing image registration toolbox.

Pattern Recognition↗
NASA NTRS2007

Research Issues in Image Registration for Remote Sensing

Image registration is an important element in data processing for remote sensing with many applications and a wide range of solutions. Despite considerable investigation the field has not settled on a definitive solution for most applications and a number of questions remain open. This article looks at selected research issues by surveying the experience of operational satellite teams, application-specific requirements for Earth science, and our experiments in the evaluation of image registration algorithms with emphasis on the comparison of algorithms for subpixel accuracy. We conclude that remote sensing applications put particular demands on image registration algorithms to take into account domain-specific knowledge of geometric transformations and image content.

Eastman, Roger D.↗
NASA NTRS1997

Spatial Distribution and Pattern Persistence of Surface Soil Moisture and Temperature Over Prairie from Remote Sensing

Images remotely sensed aboard aircraft during FIFE, namely, PBMR (microwave) soil moisture and NS001 thermal infrared surface temperature, were mapped on the same coordinate system covering the 20 km x 20 km experimental site. For both kinds of image data, the frequency distributions were close to symmetric, and the area average compared reasonably well with the ground based measurements. For any image on any given day, the correlation between the remotely sensed values and collocated ground based measurements over the area was usually high in the case of NS001 surface temperature but low in the case of PBMR soil moisture. On the other hand, at any given flux station the correlation between the PBMR and gravimetric soil moisture over all available days was usually high. The correlation pixel by pixel between images of PBMR on different days was generally high. The preservation of the spatial patterns of soil moisture was also evaluated by considering the correlation station by station between ground-based soil moisture measurements on different days; no persistence of spatial pattern was apparent during wet periods, but a definite pattern gradually established itself toward the end of each drying episode. The spatial patterns of surface temperature revealed by NS001 were not preserved even within a single day. The cross-correlations among the two kinds of images and the vegetation index NDVI were normally poor. This suggests that different processes of vegetation growth, and of the near-surface soil water and energy budgets.

Chen, Daoyi↗
NASA NTRS1996

Wideband Interferometric Sensing and Imaging Polarimetry

Wideband Interferometric Sensing and Imaging Polarimetry (WISIP) has become an important, indispensible tool in wide area military surveillance and global environmental monitoring of the terrestrial and planetary covers. It enables dynamic, real time optimal feature extraction of significant characteristics of desirable targets and/or target sections with simultaneous suppression of undesirable background clutter and propagation path speckle at hitherto unknown clarity and never before achieved quality. WISIP may be adopted to the detection, recognition, and identification (DRI) of any stationary, moving or vibrating targets or distributed scatterer segments versus arbitrary stationary, dynamical changing and/or moving geo-physical/ecological environments, provided the instantaneous 2x2 phasor and 4x4 power density matrices for forward propagation/backward scattering, respectively, can be measured with sufficient accuracy. For example, the DRI of stealthy, dynamically moving inhomogeneous volumetric scatter environments such as precipitation scatter, the ocean/sea/lake surface boundary layers, the littoral coastal surf zones, pack ice and snow or vegetative canopies, dry sands and soils, etc. can now be successfully realized. A comprehensive overview is presented on how these modern high resolution/precision, complete polarimetric co-registered signature sensing and imaging techniques, complemented by full integration of novel navigational electronic tools, such as DGPS, will advance electromagnetic vector wave sensing and imaging towards the limits of physical realization. Various examples utilizing the most recent image data take sets of airborne, space shuttle, and satellite imaging systems demonstrate the utility of WISIP.

Verdi, James Salvatore↗
NASA NTRS2019

Optical Imaging and Sensing in Harsh Environments

The paper discusses extraction of images and sensing information from targets located in harsh planetary environments. Various configuration of sensing systems with fiber optic image conduit are presented and discussed including some experimental data. Prototypes are designed and their performance are demonstrated with the focus on their potential applications in the Venusian atmosphere.

sensing↗
NASA NTRS2015

Shearlet Features for Registration of Remotely Sensed Multitemporal Images

We investigate the role of anisotropic feature extraction methods for automatic image registration of remotely sensed multitemporal images. Building on the classical use of wavelets in image registration, we develop an algorithm based on shearlets, a mathematical generalization of wavelets that offers increased directional sensitivity. Initial experimental results on LANDSAT images are presented, which indicate superior performance of the shearlet algorithm when compared to classical wavelet algorithms.

Science data processing↗
NASA NTRS2015

Shearlet Features for Registration of Remotely Sensed Multitemporal Images

We investigate the role of anisotropic feature extraction methods for automatic image registration of remotely sensed multitemporal images. Building on the classical use of wavelets in image registration, we develop an algorithm based on shearlets, a mathematical generalization of wavelets that offers increased directional sensitivity. Experimental results on multitemporal Landsat images are presented, which indicate superior performance of the shearlet algorithm when compared to classical wavelet algorithms.

Science Data Processing↗