【摘要】：隨著航天與電子產(chǎn)業(yè)的發(fā)展,光學(xué)衛(wèi)星數(shù)量不斷增加,傳感器技術(shù)不斷提升,遙感影像分辨率極大提高,單景遙感影像的數(shù)據(jù)量已經(jīng)越來越龐大。近年來我國的資源系列衛(wèi)星產(chǎn)生了海量的高分辨率遙感影像,快速有效的實(shí)現(xiàn)這些數(shù)據(jù)共享,必將推動(dòng)遙感在各行業(yè)研究與應(yīng)用的發(fā)展。面向高分辨率遙感影像,傳統(tǒng)的共享方式已經(jīng)不適用,分布式計(jì)算環(huán)境下的快速共享大趨所至。本論文從數(shù)據(jù)組織管理和傳輸,對(duì)遙感影像共享一些關(guān)鍵技術(shù)進(jìn)行研究,論文主要工作包括:1.在分析三種常用遙感影像重采樣算法的基礎(chǔ)上,改進(jìn)了一種基于距離加權(quán)和灰度值線性拉伸的重采樣算法(RADL),該算法在保證計(jì)算性能的前提下對(duì)采樣精度進(jìn)行優(yōu)化。2.在分析四叉樹切片和順序分塊切片的計(jì)算性能基礎(chǔ)上,發(fā)展了一種與順序分塊切片相結(jié)合的構(gòu)建影像金字塔的四叉樹編碼方法,并對(duì)該編碼方法下影像切片檢索展開分析。3.引入CUDA技術(shù),對(duì)影像重采樣的計(jì)算模式進(jìn)行改進(jìn),并對(duì)計(jì)算過程耗時(shí)具體分析,發(fā)展了一種基于閾值選擇計(jì)算模式的快速影像金字塔創(chuàng)建方法。4.搭建一種P2P模式下影像快速傳輸體系,并設(shè)計(jì)服務(wù)端集群和客戶端集群任務(wù)調(diào)度的負(fù)載均衡機(jī)制,結(jié)合具體行業(yè)應(yīng)用需求開發(fā)了原型系統(tǒng)。本文在RADL算法中,取得了PNSR提高9%的實(shí)驗(yàn)效果;在閾值選擇計(jì)算模式的快速影像金字塔創(chuàng)建方法中,取得了相對(duì)傳統(tǒng)四叉樹計(jì)算模式12倍的加速效果,相對(duì)CUDA計(jì)算模式1.2倍的加速效果;在影像傳輸,取得了并發(fā)請(qǐng)求客戶端數(shù)量增加,影像分發(fā)速率近似線性增加的效果,并且CPU使用率趨于平緩。上述關(guān)鍵技術(shù),廣泛應(yīng)用于遙感數(shù)據(jù)快速共享平臺(tái),以網(wǎng)絡(luò)發(fā)布方式向行業(yè)用戶提供數(shù)據(jù)和產(chǎn)品服務(wù)。
[Abstract]:With the development of aerospace and electronic industry, the number of optical satellites is increasing, the sensor technology is improving, the resolution of remote sensing image is greatly improved, and the data volume of single-scene remote sensing image has become more and more large. In recent years, our country's resource series satellite has produced massive high resolution remote sensing image, the fast and effective realization of these data sharing will promote the development of remote sensing research and application in various industries. For high resolution remote sensing images, the traditional sharing method is no longer applicable, and the fast sharing trend in distributed computing environment is becoming more and more important. This paper studies some key technologies of remote sensing image sharing from data organization, management and transmission. The main work of this paper includes: 1. Based on the analysis of three common resampling algorithms for remote sensing images, this paper improves a resampling algorithm (RADL), based on distance weighting and linear stretching of gray values. The algorithm optimizes the sampling accuracy on the premise of ensuring the computational performance. 2. On the basis of analyzing the computational performance of quadtree slice and sequential block slice, a quadtree coding method combining with sequential block slice to construct image pyramid is developed, and the image slice retrieval under this coding method is analyzed. 3. This paper introduces CUDA technology to improve the computing mode of image resampling, and analyzes the time consuming in the calculation process, and develops a fast image pyramid building method based on threshold selection computing mode. 4. A fast image transmission system in P2P mode is built, and the load balancing mechanism of server cluster and client cluster task scheduling is designed, and the prototype system is developed according to the specific industry application requirements. In this paper, the experimental effect of PNSR is improved by 9% in RADL algorithm. In the fast image pyramid creation method of threshold selection computing mode, the acceleration effect is 12 times that of traditional quadtree computing mode and 1.2 times that of CUDA computing mode. In image transmission, the number of concurrent request clients increases, the image distribution rate increases linearly, and the CPU usage rate tends to be flat. These key technologies are widely used in the rapid sharing platform of remote sensing data and provide data and product services to industry users by means of network publishing.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：P237

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本文編號(hào)：2343953