Super-resolution enhancement of UAV images based on fractional calculus and POCS

Abstract

A super-resolution enhancement algorithm was proposed based on the combination of fractional calculus and Projection onto Convex Sets (POCS) for unmanned aerial vehicles (UAVs) images. The representative problems of UAV images including motion blur, fisheye effect distortion, overexposed, and so on can be improved by the proposed algorithm. The fractional calculus operator is used to enhance the high-resolution and low-resolution reference frames for POCS. The affine transformation parameters between low-resolution images and reference frame are calculated by Scale Invariant Feature Transform (SIFT) for matching. The point spread function of POCS is simulated by a fractional integral filter instead of Gaussian filter for more clarity of texture and detail. The objective indices and subjective effect are compared between the proposed and other methods. The experimental results indicate that the proposed method outperforms other algorithms in most cases, especially in the structure and detail clarity of the reconstructed images.     

Soil salinity and vegetation cover change detection from multi-temporal remotely sensed imagery in Al Hassa Oasis in Saudi Arabia

Detecting soil salinity changes and its impact on vegetation cover are necessary to understand the relationships between these changes in vegetation cover. This study aims to determine the changes in soil salinity and vegetation cover in Al Hassa Oasis over the past 28 years and investigates whether the salinity change causing the change in vegetation cover. Landsat time series data of years 1985, 2000 and 2013 were used to generate Normalized Difference Vegetation Index (NDVI) and Soil Salinity Index (SI) images, which were then used in image differencing to identify vegetation and salinity change/no-change for two periods. Soil salinity during 2000–2013 exhibits much higher increase compared to 1985–2000, while the vegetation cover declined to 6.31% for the same period. Additionally, highly significant (p < 0.0001) negative relationships found between the NDVI and SI differencing images, confirmed the potential long-term linkage between the changes in soil salinity and vegetation cover.     

Fuel type mapping using object-based image analysis of DMC and Landsat-8 OLI imagery

Efficient forest fire management requires precise and up-to-date knowledge regarding the composition and spatial distribution of forest fuels at various spatial and temporal scales. Fuel-type maps are essential for effective fire prevention strategies planning, as well as the alleviation of the environmental impacts of potential wildfire events. The aim of this study was to assess and compare the potential of Disaster Monitoring Constellation and Landsat-8 OLI satellite images (Operational Land Imager), combined with Object-Based Image Analysis (GEOBIA), in operational mapping of the Mediterranean fuel types at a regional scale. The results showcase that although the images of both sensors can be used with GEOBIA analysis for the generation of accurate fuel-type maps, only the OLI images can be considered as applicable for regional mapping of the Mediterranean fuel types on an operational basis.     

ASTER mapping of gypsum deposits of Thumrait region of southern Oman

This study demonstrates the use of ASTER data for the mapping of gypsum deposits and associated geological formations that occurred in the Thumrait region of southern Oman. The measurement of spectra over samples of gypsum in the 1,300–2,500 nm wavelength using a PIMA spectrometer showed the presence of distinct absorptions at 1400–1600, 1750, 1940, 2,100, and 2,400 nm characteristics to O? H stretching, H₂O combinations, and S? O bending overtones and stretching, respectively. Studying the unique spectral absorption characters of gypsum samples, we developed a false color composite (FCC) and an image by decorrelation stretch using the spectral bands 7, 3, and 2 of ASTER. The results FCC showed the regions of gypsum occurrences, and the decorrelated image discriminated the gypsum occurrences from other geological formations of the area. The study of surface mineralogy of the region using the VNIR‐SWIR bands by the spectral angle mapper method showed the presence of sulfate, carbonate, and clay minerals of the geological formations in the study area. We compared the results of ASTER with the results obtained using spectral bands 12, 8, and 4 of Sentinel‐2A processed by the same methods. The study showed that the spectral bands of ASTER can be used for mapping the gypsum and associated geological formations.     

基于多源遥感影像的长春市城市建成区提取

夜光遥感影像记录的城市灯光与人类活动密切相关,已广泛应用于城市信息提取。珞珈一号作为新一代夜光遥感数据源,比以往的夜光数据具有更高的空间分辨率和光谱分辨率,可以更清晰地表达城市建成区范围和内部结构。本文利用珞珈一号夜光遥感影像,通过人类居住指数（human settlement index, HSI）、植被覆盖和建筑共同校正的城市夜光指数（vegetation and build adjusted nighttime light urban index, VBANUI）及支持向量机（support vector machine, SVM）监督分类3种方法对长春市城市建成区进行提取,并与利用NPP/VIIRS（suomi national polar-orbiting partnership/visible infrared imaging radiometer suite）夜光遥感影像、采用同样方法得到的结果对比。结果显示：本文提出的VBANUI提高了传统植被覆盖校正的城市夜光指数（vegetation adjusted nighttime light urban index, VANUI）的提取精度,使用珞珈一号夜光遥感影像通过VBANUI提取的城市建成区结果最优,其Kappa系数为0.80,总体分类精度为90.74%;使用珞珈一号和NPP/VIIRS夜光遥感影像通过HSI按最佳阈值提取城市建成区的Kappa系数分别为0.75和0.72,总体分类精度分别为88.27%和86.54%;复合数据的SVM监督分类法中Landsat-NDBI、Landsat-NDBI-VIIRS、Landsat-NDBI-LJ和Landsat-NDBI-LJlog的Kappa系数分别为0.602、0.627、0.643和0.681,总体分类精度分别为81.11%、81.52%、82.25%和84.48%。研究结果表明：3种提取方法下,均为使用珞珈一号夜光遥感影像的结果优于使用NPP/VIIRS夜光遥感影像的结果,证明相比于NPP/VIIRS夜光遥感影像,珞珈一号夜光遥感影像更适用于城市尺度的建成区范围提取。     

基于镜像图的LRC和CRC偏差结合的人脸识别

为了提高人脸识别率及更好地显示人脸特征,本文提出了一种基于镜像图的LRC和CRC偏差结合的人脸识别方法.该方法首先生成一种镜像人脸,再通过融合原始人脸和镜像人脸形成新的混合训练样本,最后利用LRC和CRC偏差结合进行人脸识别.新方法增加了训练样本的数目,克服了由于光照和姿态等外部因素带来的影响.实验结果表明,镜像图与LRC和CRC偏差结合的人脸识别方法提高了人脸识别的准确性.     

基于图像处理的自动野外救援系统设计

针对野外救援的不及时性,结合人工智能等技术的应用,提出了一种新的自动野外救援系统.人类在野外和海上活动中受困后,除了依靠自身能力和装备进行求生之外,外部的有效及时救援是提高生存几率的关键.自动野外救援系统,由自动报警装置、手动报警装置实现报警,触发整个系统的运行.自动救援装置可以通过定位模块实现定位,通过执行器移动到随身装置附近实现救援,随身装置还可以发出信标导引信号;自动救援装置还可以通过传感器检测信标,通过相位检测技术等计算待救者的坐标并规划路径,实现更精准的定位与救援.     

基于模糊熵的GLLE熵阈值分割方法

图像分割是计算机视觉中基础且重要的一个问题.熵阈值图像分割作为一种有效的分割方法,被广泛应用于模式识别和图像处理中.传统的图像分割方法并不能获得足够有效的图像特征.为解决这个问题且进一步探究熵阈值在图像分割中的应用,引入一种GLLE（Gray Level and Local Entropy）二维直方图改进熵阈值图像分割模型,并提出了基于模糊熵的方法计算所建立的二维直方图模型.通过标准实验数据集上的对比实验表明,基于模糊熵的GLLE熵阈值分割方法可以得到更加准确的阈值,提高了分割精度.同时在处理不同类型图像的表现上优于往常的算法,具有更强的鲁棒性.     

苏州水乡古镇旅游形象定位研究——以部分水乡古镇为例

古镇旅游是当今旅游市场的新宠,苏州市水乡古镇众多,特色各异,为其水乡古镇旅游发展奠定了良好的资源基础.然而,基于水乡古镇旅游产品的趋同性,使得苏州水乡古镇在旅游业发展中竞争十分激烈,旅游形象战略成为各水乡古镇旅游业可持续发展的重要战略之一.文章从苏州各水乡古镇的旅游形象宣传口号出发,对部分水乡古镇旅游形象定位进行了对比分析,在此基础上,确定了苏州水乡古镇旅游形象定位的原则,提出旅游形象定位的建议,以期促进其旅游业的协调和可持续发展.     

基于显著性图像与纹理特征的遥感影像云检测

遥感影像云检测是遥感影像处理中非常关键的环节,准确识别影像含云区域能够提升影像的利用价值.根据遥感影像的成像特点,将阈值法和纹理特征结合实现云和下垫面的分割.首先将影像从RGB(red-green-blue)空间转化为HSI(hue-saturation-intensity)空间,进而构建影像的显著性图像,利用Otsu...