A multipixel, Mueller matrix-based, unsupervised classification algorithm of polarimetric SAR images is proposed. This algorithm is based on a decision formed by the majority of pixel properties derived from the Mueller matrix within a moving window during the classification of the pixel of interest (or the center pixel of the window) . The pixels in an image are classified into three simple scattering types, odd and even number of reflections, and diffuse scattering. This algorithm decreases the unclassified pixels and improves the resultant image smoothness. First, the amplitude scattering matrix is used to calculate the corresponding Mueller matrices for each pixel. The pixel properties of all pixels in a window are then calculated and used to make a decision based on the majority of pixel properties. If all pixels or more than N/2 pixels (or more than 50% of pixels, where N is the number of pixels in a window) in a window are classified into one category, then the pixel of interest will be classified into the same category. Another criterion is added for diffuse scattering. If the pixel properties are completely random, the pixel property of interest will still be placed in the diffuse scattering category. This kind of scattering behavior may occur in forested areas. If a moving window contains no significant pixel property belonging to the categories mentioned above, then the pixel property of interest is unclassified. The window is then moved, and this process is repeated.
Generally, Human motion analysis has been performed under the condition that the camera position and the rotation are fixed. Furthermore, the human motion analysis is performed within the limited space. However, in order to analyze the most natural human motion, limitations for camera and space should be removed. For this ideal condition, some problems should be resolved. These problems include camera parameters while tracking, real-time imaging, auto tracking moving object, 3D data acquisition, and synchronization of video image sequences and camera rotation parameters while tracking. With this objective and for multiple applications such as 3D objects modeling and so on, Hybrid Video Theodolite (HVT) system was developed by the authors. The applications of the HVT system for dynamic analysis of human gait motion are investigated in this paper.
This paper describes the making method of reference reflectance panels in the case of field observation. We discussed examinations of coating materials and painting methods in order to define the making method of reference panels. As for the quality of our produced reference panel, we carried out the bidirectional reflectance factor (BRF) measurement referred to the calibrated standard panel and the bidirectional reflectance distribution function (BRDF) calibration for the reference panel. The characteristic of our produced reference panel was confirmed to have almost same as the standard panel through our experiments.
Recently, the number of pixels for consumer digital still camera are amazingly increasing by development of modern semiconductor and digital technology. The biggest pixel as a consumer digital camera was 0.8 millions at the August 1996, and transmission techniques of image to PC had been received attention. Only 4 years later, at the end of October 2000, there are 25 kinds of consumer pixel cameras on the market which have more than 3 million pixels in Japan. The functionary for transmission of image to PC is standardized, and the price is less than 1000 US$. In these circumstances, it is expected that 3 million consumer digital still cameras will become useful tool in various digital photogrammetric fields, e.g. industry, machine and robot vision, archeology, architecture, construction management, and so on. With this motive, performance evaluation of 3 million consumer pixel cameras for digital photogrammetry are investigated in this paper.