A Rapid Parallel Mosaicking Algorithm for Massive Remote Sensing Images Utilizing Read Filtering

Mosaicking is a crucial step in the application of remote sensing images. The amount of remote sensing image data has grown rapidly, along with the expansion of observed areas and increased image resolution. As a result, traditional serial mosaicking techniques are facing significant challenges. In recent times, various studies have utilized high-performance computing to hasten image mosaicking and attain favorable outcomes. Nevertheless, the current research only accelerates mosaicking through external technology, without optimizing from the perspective of algorithm flow, which introduces unnecessary data I/O and slows down the mosaicking. This paper introduces a rapid parallel remote sensing image mosaicking algorithm utilizing read filtering. To begin with, the target images are divided into blocks and stored in a distributed file system. Subsequently, the image blocks are read and filtered based on a designated input format. Finally, the overlapping and non-overlapping areas are read and processed asynchronously, reducing the data I/O and computing overhead, thereby improving the efficiency of parallel computing. The experiments indicate that the mosaicking algorithm introduced in this paper enhances throughput and speedup by an average of 1.38 MB/S and 0.87 relative to the current techniques, respectively, concerning various datasets and cores. This study provides a theoretical foundation and novel ideas for processing remote sensing images on cluster platforms.</p

Automation of region specific scanning for real time medical systems

Includes abstract.Includes bibliographical references.X-rays have played a vital role in both the medical and security sectors. However, there is a limit to the amount of radiation a body can receive before it becomes a health risk. Modern low dose x-ray devices operate using a c-arm which moves across the entire human body. This research reduces the radiation applied to the human body by isolating the region that needs exposure. The medical scanner that this work is based on is still under development and therefore a prototype of the scanner is developed for running simulations. A camera is attached onto the prototype and used to point out the regions that are required to be scanned. This is both faster and more accurate than the traditional method of manually specifying the areas

A Vision System for Automating Municipal Waste Collection

This thesis describes an industry need to make municipal waste collection more efficient. In an attempt to solve this need Waterloo Controls Inc. and a research team at UWO are exploring the idea of combining a vision system and a robotic arm to complete the waste collection process. The system as a whole is described during the introduction section of this report, but the specific goal of this thesis was the development of the vision system component. This component is the main contribution of this thesis and consists of a candidate selection step followed by a verification step