Maximum likelihood estimation of cloud height from multi-angle satellite imagery
نویسندگان
چکیده
منابع مشابه
Maximum Likelihood Estimation of Cloud Height from Multi-angle Satellite Imagery
We develop a new estimation technique for recovering depth-offield from multiple stereo images. Depth-of-field is estimated by determining the shift in image location resulting from different camera viewpoints. When this shift is not divisible by pixel width, the multiple stereo images can be combined to form a super-resolution image. By modeling this super-resolution image as a realization of ...
متن کاملFusion of Ikonos Imagery Based on Maximum Likelihood Estimation
In order to improve the fusion quality of IKONOS multispectral (MS) and panchromatic (Pan) images, this paper proposes a fusion method using maximum likelihood (ML) estimation. The proposed method firstly uses the sensor characteristics to model the observation process of both MS and Pan images. Then, the cost function with respect to the estimated high-resolution MS images is constructed based...
متن کاملMulti-channel Maximum Likelihood Sequence Estimation
In mobile radio communications, antenna arrays can be used to improve the quality and/or the capacity of the communication system. The combination of an antenna array and maximum likelihood sequence detection (MLSE) is studied here. Diierent realizations of the multi-channel MLSE are presented. Although equivalent in performance, it is pointed out that one of them, the multi-dimensional matched...
متن کاملAngle of Arrival Estimation Using Maximum Likelihood Method
Abstract—Multiple-input multiple-output (MIMO) radar has received increasing attention in recent years. MIMO radar has many advantages over conventional phased array radar such as target detection,resolution enhancement, and interference suppression. In this paper, the results are presented from a simulation study of MIMO uniformly-spaced linear array (ULA) antennas. The performance is investig...
متن کاملMaximum Likelihood Estimation of Parameters in Generalized Functional Linear Model
Sometimes, in practice, data are a function of another variable, which is called functional data. If the scalar response variable is categorical or discrete, and the covariates are functional, then a generalized functional linear model is used to analyze this type of data. In this paper, a truncated generalized functional linear model is studied and a maximum likelihood approach is used to esti...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Annals of Applied Statistics
سال: 2009
ISSN: 1932-6157
DOI: 10.1214/09-aoas243