Real-Time Detection, Registration and Recognition Using Pixel-Level Fusion of Active/Passive Imagery

نویسندگان

  • Alan N. Steinberg
  • Robert Pack
چکیده

A system has been developed whereby active ladar and passive electro-optic imaging data are aligned in hardware at the pixel level. The resulting arrays of fully aligned, high-dimension feature data permit dense point matching in three spatial dimensions for enhanced real-time detection, registration and target recognition. Military applications for which this technology is being developed or assessed include precision tactical targeting, Precision Controlled Reference Image Base (CRIB) production and automatic registration of targeting data into the CRIB. Civil applications include 3D city modelling, real-time airborne mapping, post-disaster reconnaissance, floodplain and coastline mapping, drug interdiction target detection, environmental monitoring, and search and rescue. The system combines the ability of active systems to work at long ranges and to penetrate obscurants with the passive arrayís wide instantaneous field of view at increased resolution. This has been found to enormous benefit is in observation through partial or intermittent obscuration; e.g. with partial cloud cover or foliage.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Toward Target Verification Through 3-D Model-Based Sensor Fusion

Most Automatic Target Recognition (ATR) algorithms operate in 2D image space. Even when using 3D models, these 3D models are typically translated o -line into sets of 2D representations, such as templates, which are then applied to imagery to perform detection, recognition and veri cation. In contrast to this approach, the work reported here takes steps toward direct matching of 3D models to ra...

متن کامل

Hyperspectral Algorithm Development for Military Applications: A Multiple Fusion Approach

Developments of long range target detection techniques have been a military priority, especially against very low observable targets like deeply hidden vehicles. Not surprisingly, the need for the development of a highly efficient passive detection system with sensitivity capable to detect extremely low cross-section objects like mines is even more demanding. In this paper, we summarise the ach...

متن کامل

Application of Combined Local Object Based Features and Cluster Fusion for the Behaviors Recognition and Detection of Abnormal Behaviors

In this paper, we propose a novel framework for behaviors recognition and detection of certain types of abnormal behaviors, capable of achieving high detection rates on a variety of real-life scenes. The new proposed approach here is a combination of the location based methods and the object based ones. First, a novel approach is formulated to use optical flow and binary motion video as the loc...

متن کامل

Comparing the Capability of Sentinel 2 and Landsat 8 Satellite Imagery in Land Use and Land Cover Mapping Using Pixel-based and Object-based Classification Methods

Introduction: Having accurate and up-to-date information on the status of land use and land cover change is a key point to protecting natural resources, sustainable agriculture management and urban development. Preparing the land cover and land use maps with traditional methods is usually time and cost consuming. Nowadays satellite imagery provides the possibility to prepare these maps in less ...

متن کامل

An efficient method for cloud detection based on the feature-level fusion of Landsat-8 OLI spectral bands in deep convolutional neural network

Cloud segmentation is a critical pre-processing step for any multi-spectral satellite image application. In particular, disaster-related applications e.g., flood monitoring or rapid damage mapping, which are highly time and data-critical, require methods that produce accurate cloud masks in a short time while being able to adapt to large variations in the target domain (induced by atmospheric c...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2003