Monitoring leaf area of sugar beet using ERS-1 SAR data

This paper presents the results of field testing a radar model which relates leaf area index to radar backscatter for ERS-1 C-band VV polarization SAR data. Ground truth measurements of leaf area index and soil moisture content were made in selected sugar beet fields, with simultaneous acquisition of ERS-1 SAR image data. Radar backscatter coefficients were derived from the calibrated ERS-1 SAR data. The Leeuwen and Clevers expression of the water cloud model was fitted to determine the in situ relationship between radar back-scatter and leaf area index. The model can be inverted analytically to calculate leaf area index from radar backscatter. The results show considerable potential for the operational application of ERS-1 SAR data in crop monitoring.     

ScanSAR processing and simulation for ASAR using ERS-1 raw data

This paper presents results from a study on scanSAR processing and simulation. ERS-1 raw data in both normal mode and roll tilt mode are used for Doppler centroid estimation, processing and simulation. Azimuth gain variations and azimuth ambiguity ratios are evaluated for different scanning strategies and as a function of Doppler centroid errors. A scanning strategy with two scan cycles in each imaging cycle has been selected and a processing scheme with three range looks and two azimuth looks has been implemented. SPECAN is considered very favourable for azimuth processing because or its efficiency. The degradation in image quality is investigated by imposing individual (differential) beam pointing errors on real ERS-1 data. It is demonstrated in this work that the individual azimuth beam pointing errors should be less than 0004° to avoid visible degradations in homogeneous regions in the scanSAR image. Using many bursts and all subswaths for Doppler centroid estimation, it is assumed that Doppler centroid estimates will be so accurate that no image degradation is visible when azimuth intensity compensation is performed.     

Study of digital image processing techniques for leaf disease detection and classification

Multimedia Tools and Applications - In this paper, we address a comprehensive study on disease recognition and classification of plant leafs using image processing methods. The traditional manual...     

The identification of rice fields using multi-temporal ERS-1 C band SAR data

In this paper, an approach for the use of spaceborne SAR data for rice field identification, as well as for land use classification, is demonstrated, by using multitemporal data acquired over the Ohgata-mura area, Akita, Japan with ERS-1 C-band SAR, in 1992. Two techniques for reducing the influence of speckle on the accuracy of rice field identification were tested. A comparison of the SAR results with land use survey data collected in 1993, and with Landsat TM data, shows the potential of the present approach.     

New and efficient blind detection algorithm for digital image forgery using homomorphic image processing

Multimedia Tools and Applications - Digital image forgery detection is an important task in digital life as the image may be easily manipulated. This paper presents a novel blind tampering...     

Aspect and incidence angle sensitivity in ERS-1 SAR data

Large variations in backscattering coefficients were observed on ERS-1 SAR images acquired from ascending and descending orbits, within 36 hours, over an agricultural area and under stable winter conditions. Three possible causes were investigated: (1) environmental factors; (2) SAR processor instability; and (3) aspect and incidence angle sensitivity. The look direction (aspect angle) accounted for a 1.5dB difference in backscattering coefficients. The remaining variations were related to the incidence angle. A correction model is proposed.     

SAR image processing using adaptive stack filter

Stack filters are a special case of non-linear filters. They have a good performance for filtering images with different types of noise while preserving edges and details. A stack filter decomposes an input image into several binary images according to a set of thresholds. Each binary image is filtered by a Boolean function. The Boolean function that characterizes an adaptive stack filter is optimal and is computed from a pair of images consisting of an ideal noiseless image and its noisy version. In this work the behavior of adaptive stack filters on synthetic aperture radar (SAR) data is evaluated. With this aim, the equivalent number of looks for stack filtered data are calculated to assess the speckle noise reduction capability of this filter. Then a classification of simulated and real SAR images is carried out on data filtered with a stack filter trained with selected samples. The results of a maximum likelihood classification of these data are evaluated and compared with the results of classifying images previously filtered using the Lee and the Frost filters.     

On shock localization by digital image processing techniques

A general approach is presented to a problem of localization of strong discontinuities in the spatial domain on the basis of numerical solution of multidimensional steady and unsteady problems by finite difference shock-capturing techniques. The essence of the approach is in the use of ideas and methods of the digital image processing theory, in particular, of methods for the detection of edges in the image brightness. The algorithms of localization of strong discontinuities in the difference solutions developed on the above-mentioned basis do not require for their realization any a priori information on the orientation of shock surfaces with respect to the spatial co-ordinates axes. The questions of accuracy of the new localization algorithms and of increasing the accuracy of the numerical solutions with the aid of image restoration techniques are considered. The universality of the proposed algorithms is demonstrated in the examples of computations of a number of model two-dimensional unsteady problems by the Godunov scheme and by the MacCormack scheme.     

Mapping near-surface soil moisture on regional scale using ERS-2 SAR data

Soil moisture is an important hydrologic variable of great consequence in both natural and agricultural ecosystems. Unfortunately, it is virtually impossible to accurately assess the spatial and temporal variability of surface soil moisture using conventional, point measurement techniques. Remote sensing has the potential to provide areal estimates of soil moisture at a variety of spatial scales. This investigation evaluates the use of European Remote Sensing Satellite (ERS-2) C-band, VV polarization, synthetic aperture radar (SAR) data for regional estimates of surface soil moisture. Radar data were acquired for three contiguous ERS-2 scenes in the Southern Great Plains (SGP) region of central Oklahoma from June 1999 to October 2000. Twelve test sites (each approximately 800?m×800?m) were sampled during the ERS-2 satellite overpasses in order to monitor changes in soil moisture and vegetation on the ground. An average radar backscattering coefficient was calculated for each test site. Landsat-5 and -7 Thematic Mapper (TM) scenes of the experimental sites close in time to the ERS-2 acquisition dates were also analysed. The TM scenes were used to monitor land cover changes and to calculate the Normalized Difference Vegetation Index (NDVI). Land cover and ground data were used to interpret the radar-derived soil moisture data. Linear relationships between soil moisture and the backscattering coefficient were established. Using these equations, soil moisture maps of the Little Washita and the El Reno test areas were produced.     

Iceberg detection using ERS-1 Synthetic Aperture Radar

We review the importance of iceberg monitoring and the current status of iceberg detection methods using spaceborne synthetic aperture radar, and describe the newly developed iceberg detection subsystem of the Ice Pilot Application Project sea ice system. Validation against in situ data from the European high Arctic and the North Atlantic near Newfoundland suggests that the subsystem is able to detect about half of all icebergs between 15 and 60 m across, and virtually all icebergs larger than 120 m across, under calm, sea-ice-free conditions.     

Mapping tropical coastal vegetation using JERS-1 and ERS-1 radar data with a decision tree classifier

The objective of this paper is to investigate the complementarity of JERS-1 and ERS-1 data for mapping coastal tropical regions. We use a decision tree classifier to classify a coastal region of Gabon and describe the feature contribution using the decision tree diagram. The JERS-1 Global Rain Forest Mapping (GRFM) and ERS-1 Central Africa Mosaic Project (CAMP) datasets are used. The result is a land cover map of the west coast of Gabon. The analysis explicitly shows the complementary characteristics of the L- and C-band Synthetic Aperture Radar (SAR) instruments. We demonstrate the usefulness of combined use of L- and C-band data for large area mapping of coastal regions, especially in flooded areas for discrimination of high and low mangroves as well as grasses and tree swamps. The overall classification accuracy increases by 18% over single band classification.     

Comparison of the detection of deforested areas using the ERS-1 ATSR and the NOAA-11 AVHRR with reference to ERS-1 SAR data: a case study in the Brazilian Amazon

Two coarse spatial resolution classifications of nominally 1·1 km resolution of deforested areas over a test site covering part of the south-west Amazon basin are compared. One classification is derived from data acquired by NOAA's Advanced Very High Resolution Radiometer (AVHRR) and the other from the ERS-1 Along Track Scanning Radiometer (ATSR-1). A forest/non-forest classification derived from finer spatial resolution ERS-1 Synthetic Aperture Radar (SAR) data is used as a reference for the comparison. Specific patterns of deforestation in the area are identified and their depiction on each of the coarse spatial resolution datasets is examined in relation to their depiction on the fine spatial resolution classification. The results show that significant differences exist between the two coarse spatial resolution classifications and that special rigorous integration methodologies will have to be developed before the results from either source can be used interchangeably with those from the other.     

Analysis of coastal ice cover using ERS-I SAR data

An applications demonstration of the use of Synthetic Aperture Radar (SAR) data in an operational selling is being conducted by the National Oceanic and Atmospheric Administration (NOAA) CoastWatch Program. In the development phase of this demonstration, case studies were conducted to assess the utility of SAR data for monitoring coastal ice in the Bering Sea, icebergs from calving glaciers in Prince William Sound, and lake ice in the Great Lakes. ERS-l SAR data was used in these studies. Results showed that depending on size and sea state icebergs could be detected from background and computer enhanced in the imagery, thaI SAR data can supplement and enhance the utility of satellite visible and infrared data sources for coastal ice monitoring, and that Greal Lakes ice cover can be classified by ice type and mapped in the SAR data using image processing techniques. Cloud cover was a common problem. Based on the further development of automated analysis algorithms and the increase in frequency of SAR coverage, the all-weather, day/night viewing capabilities of SAR make it a unique and valuable tool for operational ice detection and monitoring.     

基于数字图像处理技术的实时检测系统*

基于在线检测系统与图像处理算法的研究,提出了一种适用于在线检测的快速胶片弊病检测算法。采用了红外光对胶片成像,并通过CCD相机采集图像信号送入计算机,通过平滑滤波、边缘提取及累加判别等处理技术,实现了对胶片弊病的识别与检测。现场调试运行表明,在卷片机车速2070 m/min的条件下,该系统运行稳定,对于黑白胶片的各种典型弊病能够正确检测,并能忽略掉胶片上可以接受的微小瑕疵,满足了实际生产的需要。     

Procedures for change detection using Landsat digital data

Resource management agencies are interested in knowing when and how satellite data can be effectively used to monitor environmental change and what information can be expected from remote sensing techniques. In this paper the procedures that might be followed in applying the complementary methods of band ratioing and post-classification change detection to monitor a large remote area are outlined. Examples from research in the Peace-Athabasca Delta are used to illustrate the procedures and expected results.     

Characterization of blood samples using image processing techniques

This paper presents a methodology to determine human blood types in an emergency situation as well as a reliability study of the methodology proposed. The plate test is employed to determine blood types, allowing the macroscopic results observation. A CCD camera captures an image of the plate test results that will be processed through image processing techniques available in the IMAQ Vision software from National Instruments. The techniques used in this work are able to determine the occurrence of agglutination allowing the determination of blood types with an algorithm of classification. The reliability study based on statistical tests determines the level of confidence of the approach. The equipment developed is able to automatically perform the plate test and determine blood types.     

Digital elevation model generation using ascending and descending ERS-1/ERS-2 tandem data

In this study we show how ascending and descending ERS-1/ERS-2 tandem data can be used to generate a precise digital elevation model (DEM). In particular we present the advantages, for DEM generation, of combining ascending and descending interferometric data pairs with large baselines; unwrapping problems caused by the high fringe rates of these data are minimized by applying a flattening technique based on the use of a data pair with smaller baseline. The presented experiments carried out on the data of an area with steep topography (Etna volcano, Italy) confirm the potentiality of the proposed technique.     

Evaluation and digital processing of multispectral SPOT data

Abstract

On the basis of multispectral SPOT data of a test site in southern Algeria(Djebel Amour) the high correlation of the spectral bands S1 and S2 (green and red) could be demonstrated. Due to this fact, the geological application possibilities by means of standard products (e.g. false colour composite) are strongly decreased. The application of advanced image processing techniques on the basis of the I-H-S colour transform, however, enable an improved presentation of subtle spectral differences and, therefore, a better differentiation of geologically relevant phenomena.     

采用数字图像处理技术的条干均匀度在线检测系统

为了实现测量过程的自动化,提出了应用图像处理技术的条状物均匀度在线检测系统的设计方法。以交叉编译开发环境Qt Creator为核心,结合开源图像处理库OpenCV,实现了不规则条状物外尺寸的非接触式在线测量和实时显示。采用显微放大镜头,搭建了专用的光学系统;图像预处理采用最大类间方差法(Otsu),消除了不同光照强度对检测结果的影响;为了充分体现人机交互性而编写了友善的上位显示界面,采用MATLAB对采集到的数据进行曲线拟合,验证了分段直线拟合的可行性。实验结果表明,该装置结构简单,测量结果准确,使纺织品条干均匀度在线实时检测成为可能。