Study of the lidar measurement is very significant in a variety of applications including forest remote sensing. Among them, polarimetric lidar is a relatively new but important active remote sensing tool. This study covers a comprehensive description of the system performance of both the polarimetric lidar and non-polarimetric lidar. Noticeably, relative performances of both lidar systems can be estimated exploiting several classifiers such as artificial neural network, k-NN (k-nearest neighbor) classifier and the discriminant function. In each of these attitudes, the principal aspect is to compare the classification results obtained by different classifiers to obtain improved lidar performance. In this case, utility of polarimetric and non-polarimetric waveform features for classification was tested using a group of randomly selected trees such as pines, elm, blue spruce, maple, choke cherry, and green ash. The k-NN classifier obtained 92% accuracy using non-polarimetric data. However, for k-NN classifier the value of k is provided by the user. Strikingly, same k-NN classifier achieved 96 % accuracy using polarimetric data. Again, artificial neural network classifier achieved 96% classification accuracy using polarimetric lidar data whereas the classification accuracy it received was around 89 % using non-polarimetric lidar data. Most poor performance was received by discriminant analysis. In case of nonpolarimetric data, discriminant analysis results in only 59 % efficiency. In contrast, about 75 % classification accuracy was observed using polarimetric data for discriminant analysis. Though the listed classifiers can perform better using polarimetric data than non-polarimetric data, artificial neural network can be employed for better performance.
A hybrid problem-based learning (h-PBL) strategy was developed and executed in a digital image processing (DIP) course at the South Dakota State University. The newly developed curriculum encompasses the design and implementation of a problem-based learning (PBL) project: a three dimensional (3D) imaging project using fringe projection. The PBL project requires students to build a digital fringe projection system using a digital projector, to use a digital camera to capture the deformed fringe patterns projected onto the object under study, and to process the captured images using the software Matlab in order to retrieve the 3D profile of the object. The course was taught in a hybrid fashion with a mixture of both traditional lecturing (TL) and PBL, to replace the previous TL course. This paper presents the curriculum development activity and investigates the student perspectives on the developed h-PBL approach through a survey study. Longitudinal data from the open-ended surveys administered after the completion of the PBL project were collected from the multiple year study of the DIP course taught by the same instructor. Data analysis reveals that a higher level of student satisfaction was achieved after h-PBL. The h-PBL approach, albeit more challenging and time-consuming in comparison with TL, motivated and stimulated student self-regulated learning, improved student problem solving skill, and promoted student critical thinking.
Vegetation stress detection is of great importance to many agricultural and ecological studies. Vegetation water stress is commonly encountered in many areas. The accurate detection of water stress may enable more efficient use of limited water resource. Plant leaf water content is also one of the primary factors indicating vegetation health condition. In this study, a polarized laser at 532-nm was used to study water stress from plant leaves. Polarimetric measurements of the backscattered light were conducted. Preliminary study indicates that depolarization ratio is a good indicator of water stress in the studied case. In addition, an overall increasing trend of depolarization ratio under water stress condition was also observed.
Digital watermarking is an important technique to protect copyrighted multimedia data. This technique works by hiding secret information into the images. Therefore, it can be used to discourage illicit copying or distribution of copyrighted materials. In this paper, we propose a robust frequency domain digital watermarking algorithm for still image based on discrete cosine transformation. Adjustable parameters are introduced during the watermark embedding process, which adaptively change the JPEG quantization factor, as well as the depth at which the watermark is embedded. The proposed watermarking technique still maintains its validity under certain image processing operations such as low pass filtering, image cropping, etc. Compared with previous method, however, it has improved performance under Joint Photographic Experts Group (JPEG) compression attack. The extracted watermark maintains its high quality in terms of normalized correlation even under a high JPEG compression ratio.
There is a growing interest toward using lidar for forest remote sensing. The Multiwavelength Airborne Polarimetric Lidar (MAPL) was designed primarily for vegetation remote sensing purposes. The system has full lidar waveform capture and polarimetric measurement capabilities at 532-nm and 1064-nm wavelengths. To study the polarimetric reflectance from different tree species, ground experiments were conducted using the MAPL system. Three tree canopies with distinct features were selected for this study. These are cottonwood (Populus deltoides), black willow (Salix nigra) and red-cedar (Juniperus virginiana). The test results revealed that the shapes of the lidar waveforms, the depolarization ratios, and the percent reflectance data all have distinct features for different tree species. The MAPL system is proved to be able to detect all these features. Our study indicates that the MAPL data have the potential to be used toward developing a tree species discrimination algorithm. In addition, it is also believed that these data can be used to detect tree stress conditions.
Laser radar systems have found wide applications in the field of remote sensing. Reflectance as well as polarization features are used together for applications ranging from environmental monitoring to target classification. The Stokes parameters are ideal quantities for characterizing the above features because they provide useful information on both light intensity and polarization state. The University of Nebraska is currently refurbishing an airborne multi-wavelength laser radar system based on the NASA Goddard Space Flight Center (GSFC) developed Airborne Laser Polarimetric Sensor (ALPS). The system uses a Nd:YAG laser operating at wavelengths of 1064 nm and 532 nm, and contains four channels at each wavelength to measure the polarization states. This system was used to measure the Stokes parameters of backscattered laser light from different materials. These included canvas tarp, white paper, plywood, concrete, aluminum plate and anodized aluminum plate. The data provide an understanding of the polarized scattering properties of various materials, and are expected to be useful in developing target discrimination algorithms.