CBERS-1卫星02号星图像MTF复原及其结果分析评价

对退化图像进行信息恢复是遥感图像处理的研究重点。本文从刀刃曲线求取MTF的基本理论入手,对灰度图像上的特定纹理等间隔采样,插值拟和刀刃曲线从而求得线扩散函数(LSF)。将线扩散函数进行傅立叶变换得到MTF后,在频域内对退化图像进行逆变换后再将频域里的图像进行傅立叶逆变换得到恢复后的遥感图像,在频域中对图像进行恢复的关键处理在于把图像的最高频率和光学截止频率对应起来。本文除列出对比退化较之恢复图像的定量指标外,还定性地提出了恢复前后图像的傅立叶变换的频谱、地物分类情况同亮度的直方图统计等方法,更直观地评价了实验结果。该方法应用于CBERS-1的02号卫星图像,恢复后图像的边缘清晰度与细节的详细程度较之退化图像有了很明显的改善。     

基于小波变换的CBERS-02图像薄云薄雾去除的方法研究

大气活动的干扰是遥感技术发展的最大限制之一,对星载的可见光、近红外波段的光学探测器而言,大气中云雾的干扰更是不易处理。为了促进CBERS-02星CCD传感器图像的定量化应用,在对以往有关遥感图像薄云去处方法的研究的基础上,本文提出了对含薄云的CBERS-02 CCD图像进行适当层次的小波分解,然后对分解的图像进行同态滤波,最后进行图像重构而去除薄云的方法。试验结果表明,该方法既能有效的去除薄云,又可较好的保持图像细节。     

无人机遥感图像中不均匀雾霾的去除算法研究

由于雾霾的存在,无人机(Unmanned Aerial Vehicle,UAV)获取的图像受到严重影响。利用单一算法很难有效地去除无人机遥感图像中不均匀的雾霾。本文提出了一种新的去雾算法,该方法将图像分割技术与暗原色方法结合起来,实现不均匀雾霾的综合去除。该方法的具体处理过程如下:首先,利用图像分割技术将原图像根据雾的浓度分为淡雾、浓雾两部分;其次,依据暗原色先验理论,获取比较准确的大气光,分别求取大气光的模、方向;再次,利用引导联合双边滤波细化透射率,针对浓雾部分利用局部视网膜皮层理论(Retina-cortex theory,Retinex)增强进一步处理,最终得到恢复的图像。实验结果表明,相比于He和Retinex算法,本文算法在图像细节还原、色彩保真等方面具有更好的处理效果。     

基于卡尔曼运动模型模糊图像恢复技术研究

提出了一种基于卡尔曼运动模型进行运动模糊图像退化过程分析的方法 ,设计了基于卡尔曼运动质量退化模型的运动模糊图像恢复算法 ,该方法逼近实际的运动模型。通过对火车称重系统中的模糊影像恢复实验 ,表明了该恢复技术的有效性     

基于暗通道先验的航拍图像去雾效果优化

航拍图像数据量大、图幅多、云雾情况复杂,在观测了大量航拍去雾图像后,发现效果并不理想,对比度依旧不高.通过研究暗通道先验去雾算法,分析有雾图像退化过程,提出了基于暗通道先验的航拍图像去雾效果优化方法.当原始图像云雾不均时,采用增强大气透射率图层对比度的方法来改善去雾输出图像的质量;此外,针对全部有雾输入图像,使用自动对...     

DMC卫星图像MTF分析及其复原方法研究

复原退化模糊图像是遥感图像处理的研究重点。对成像系统的调制传递函数(MTF)进行了研究,分析了调制传递函数的基本理论。讨论了一种近似测定成像系统调制传递函数的方法,通过有限采样,曲线拟合,傅立叶变换,规格化的一系列处理得到图像获取、传输过程中的点扩展函数(PSF)。提取完整光滑的调制传递函数曲线,在频域中对图像进行去卷积复原,分析和评价了复原结果。将该方法应用于DMC卫星图像,图像质量得到明显提高,收到较好的复原效果。     

高分辨率TDI-CCD成像数据的自适应MTF图像复原处理研究

调制传递函数(MTF)是光学成像系统性能的一个重要的综合评价指标,也是图像退化模型中最重要的部分。针对TDI-CCD成像数据的特点,从遥感图像中获取刀刃边缘来计算成像系统的MTF,采用维纳滤波法及修正的逆滤波器法(MIF)对退化图像进行MTF补偿处理。实验结果表明,高分辨率TDI-CCD成像数据经自适应MTF复原处理后,可以有效地改善图像质量。目前,该算法已成功地应用到我国国产地面卫星预处理系统中。     

雾霾天气条件下偏振遥感图像复原研究

针对雾霾天气造成图像质量退化引起的图像对比度降低问题,根据目标场景与大气气溶胶粒子散射光偏振特性的差异,开展雾霾天气目标偏振探测图像复原研究。通过实验获取雾霾天气条件下不同偏振旋转方位角度图像,提出图像复原算法进而提高图像对比度,抑制雾霾介质造成图像退化的影响,提高光学成像系统的成像质量。结果表明,此算法能有效提高图像对比度和图像信息熵值,恢复目标,同时获取了目标景物的深度信息。本文研究为雾霾天气下目标探测与识别提供了有效的技术途径。     

6S辐射传输模型在校正哈尔滨市遥感图像中的应用

由于遥感器在空中获取地表信息过程中,受到大气成分吸收与散射的影响,测量值发生辐射失真。本文通过分析大气成分对辐射传输的影响,探讨遥感图像处理中大气校正的方法。     

多暗像元大气校正方法

 针对Landsat TM影像，设计了一种适用于非均质大气的大气校正方法。该方法以暗目标减法（DOS）为基础，结合大气辐射传输模型，通过选取TM影像上多个暗像元，并计算其所对应的大气校正系数对整幅图像进行大气校正。该方法不依赖任何外部信息，并且考虑了大气的非均质性，校正精度较高。     

Robust Array Configuration for a Microwave Interferometric Radiometer: Application to the GeoSTAR Project

The Geostationary Synthetic Thinned Array Radiometer represents a promising new approach to microwave atmospheric sounding from geostationary orbit based on passive interferometry. One of the major concerns about the feasibility of this new concept is related to the ability of the sensor to cope with the failure of one or several of its single receivers/antennas. This letter shows that the inclusion of a small percentage of additional antennas significantly reduces the degradation of radiometric resolution caused by such receiver failure. Impact of antenna failure is analyzed, taking into account two test images with very different spatial harmonic content. A tradeoff analysis of several array topologies is performed so as to minimize the number of additional antennas while keeping worst case radiometric error within a reasonable level     

Azimuth resolution of spaceborne P, VHF-band SAR

A degradation of spatial resolution performance of spaceborne synthetic aperture radar (SAR) images, which is due to the atmospheric radio waves propagation effects, is considered in this letter. A special calculation procedure of spatial resolution performances, in particular of the SAR azimuth resolution, is offered. Herein, the analysis of a potential spatial resolution, resulting from the influence of the atmosphere, on SAR images is presented.     

A Model-Based Approach to Semi-Automated Reconstruction of Buildings from Aerial Images

Automated reconstruction of building objects from aerial images is a complex problem due to the diversity of buildings as well as noise and low contrast of images, which are the results of distant photography, atmospheric effects and poor illumination. In this paper, a semi-automated approach to the reconstruction of parametric building models from aerial images is presented, which works with line segments extracted from the image. The model is selected interactively from a library of parametric models. A perceptual grouping technique is used to select the most significant image lines in terms of relations such as proximity and parallelism. Model lines are searched for the same relations as in the grouped image lines, and the corresponding lines undergo a matching procedure, which determines whether or not a match can be found between the given model and image lines. An experiment with aerial images of flat-roof and gable-roof buildings is shown and its results indicate the robustness and efficiency of the proposed approach.     

不同地表覆盖下SPOT-7影像大气校正方法研究

针对不同的地物覆盖类型,分析和评价了适用于SPOT-7卫星数据的大气校正方法,为其遥感定量研究和应用提供思路和参考.在河南省嵩山地区进行了同步观测实验,获取了SPOT-7卫星影像并进行大气校正处理,地面同步测量了大气光学特性和典型地物样区光谱,计算了地物样区在影像上的反射率和植被指数,分析了不同地物覆盖类型下大气校正模...     

高分三号SAR影像广域范围联合几何检校技术

在获取广域范围雷达遥感正射影像图时,需要对区域内每景SAR影像进行几何参数修正,提高SAR影像的定位精度。但在广域范围进行控制点的选取和影像的逐一修正,其工作量巨大,严重影响了SAR影像分析应用的效率。对此,本文提出了一种广域范围联合几何检校方法。该方法在R-D模型的基础上,首先利用少许SAR影像计算其独立的系统级检校参数,其次去除系统级检校参数中大气延迟分量的影响,然后依据最小二乘平差原理获取最优的系统级检校参数,最后利用最优的系统级检校参数对所有SAR影像进行几何检校处理。论文采用覆盖中国中东部地区的32景GF-3SAR影像进行联合几何检校试验,检校后的SAR影像定位中误差优于9 m。试验结果表明:该方法能够提高GF-3 SAR影像几何检校的精度,验证了其有效性和可行性。     

Atmospheric Correction Methods for GF-1 WFV1 Data in Hazy Weather

Increasing hazy weather in the eastern area of China limits the potential application of high-resolution satellite data and poses a huge challenge for the atmospheric correction of remote sensing images. Consequently, it is necessary to find the most suitable atmospheric correction method under hazy condition. In this study, five kinds of atmospheric correction models, including 6S, COST, FLAASH, QUAC, and ATCOR2, are applied to the GaoFen-1 Wild Field Camera (GF-1 WFV1) data in the eastern area of China, and examined by both quantitative and qualitative analyses using the measured spectrum data. Experimental results indicated that ATCOR2 achieves the best performance among the atmospheric correction methods qualitatively and quantitatively. Hence, specifically for the study area and GF-1 WFV1 dataset, ATCOR2 is the most suitable atmospheric correction approach under hazy in the eastern area of China.     

以气象记录为辅助数据的TM影像大气校正方法

本文介绍一种LANDSATTM卫星影像校正方法,通过传感器校准、大气校正、地形校正等步骤获得反射率影像,卫星飞越时的大气参数是由当地气象记录的内插值导出,再以像幅内黑暗地物做调整,所用的大气传输模型为改进的Turner模型,可计算阳光直接辐照度、天光辐照度、路径亮度等参数,地形模型既可用来调整各参量随高程的变化,又可用以校正幅射的地形效应。     

Development of time series stacks of Landsat images for reconstructing forest disturbance history

Abstract

Forest dynamics is highly relevant to a broad range of earth science studies, many of which have geographic coverage ranging from regional to global scales. While the temporally dense Landsat acquisitions available in many regions provide a unique opportunity for understanding forest disturbance history dating back to 1972, large quantities of Landsat images will need to be analysed for studies at regional to global scales. This will not only require effective change detection algorithms, but also highly automated, high level preprocessing capabilities to produce images with subpixel geolocation accuracies and best achievable radiometric consistency, a status called imagery-ready-to-use (IRU). This paper describes a streamlined approach for producing IRU quality Landsat time series stacks (LTSS). This approach consists of an image selection protocol, high level preprocessing algorithms and IRU quality verification procedures. The high level preprocessing algorithms include updated radiometric calibration and atmospheric correction for calculating surface reflectance and precision registration and orthorectification routines for improving geolocation accuracy. These automated routines have been implemented in the Landsat Ecosystem Disturbance Adaptive System (LEDAPS) designed for processing large quantities of Landsat images. Some characteristics of the LTSS developed using this approach are discussed.     

Retrieval of land surface temperature (LST) from landsat TM6 and TIRS data by single channel radiative transfer algorithm using satellite and ground-based inputs

The present study proposes land surface temperature (LST) retrieval from satellite-based thermal IR data by single channel radiative transfer algorithm using atmospheric correction parameters derived from satellite-based and in-situ data and land surface emissivity (LSE) derived by a hybrid LSE model. For example, atmospheric transmittance (τ) was derived from Terra MODIS spectral radiance in atmospheric window and absorption bands, whereas the atmospheric path radiance and sky radiance were estimated using satellite- and ground-based in-situ solar radiation, geographic location and observation conditions. The hybrid LSE model which is coupled with ground-based emissivity measurements is more versatile than the previous LSE models and yields improved emissivity values by knowledge-based approach. It uses NDVI-based and NDVI Threshold method (NDVI^THM) based algorithms and field-measured emissivity values. The model is applicable for dense vegetation cover, mixed vegetation cover, bare earth including coal mining related land surface classes. The study was conducted in a coalfield of India badly affected by coal fire for decades. In a coal fire affected coalfield, LST would provide precise temperature difference between thermally anomalous coal fire pixels and background pixels to facilitate coal fire detection and monitoring. The derived LST products of the present study were compared with radiant temperature images across some of the prominent coal fire locations in the study area by graphical means and by some standard mathematical dispersion coefficients such as coefficient of variation, coefficient of quartile deviation, coefficient of quartile deviation for 3rd quartile vs. maximum temperature, coefficient of mean deviation (about median) indicating significant increase in the temperature difference among the pixels. The average temperature slope between adjacent pixels, which increases the potential of coal fire pixel detection from background pixels, is significantly larger in the derived LST products than the corresponding radiant temperature images.     

北京市平原区2015年—2019年0.8 m地表反射率数据集

地表反射率产品作为最重要的定量遥感产品,是很多参量化遥感产品的基础数据源,可以被广泛应用于林业、农业、水资源、生态环境、城市环境等典型应用领域。对于米级高分辨率的遥感影像,国内外不提供反射率影像产品。目前主流的国产高分数据源大部分都是蓝、绿、红、近红4个波段的多光谱数据,缺少短波红外波段,难以满足陆地区域浓密植被算法或者清洁水体的短波红外信号近似看作零的假设条件,要完成精确大气校正、生产大范围的GF-2影像拼接的地表反射率产品,是一个挑战。为了更好的推广高分地表反射率的应用,本研究针对北京市平原区,运用全色和多光谱融合、几何精校正和相对辐射一致化算法,以Sentinel-2为参考影像,生成了一套几何精校正后的0.8 m地表反射率影像集。该数据集时间范围为2015年—2019年,每年一期,包含年度产品的覆盖情况及分布矢量,共计184景地表反射率影像,数据量总共为1.63 TB。