本文選題：無線網(wǎng)絡(luò)傳輸系統(tǒng)　切入點：小波變換　出處：《北京郵電大學》2017年碩士論文　論文類型：學位論文

【摘要】：為了保證信息可以不受限于網(wǎng)絡(luò)、信號、安全等因素進行快速傳輸,我們與軍方合作,設(shè)計并開發(fā)了一套無線網(wǎng)絡(luò)傳輸系統(tǒng)。這套系統(tǒng)通過FPGA射頻信號傳輸加密后的信息,不會受到網(wǎng)絡(luò)、信號、安全等因素的干擾,不僅可以進行正常通信,還可以用來進行野外救援、作戰(zhàn)指揮等。當前系統(tǒng)主要由業(yè)務(wù)平臺和無線平臺兩個部分組成�；谶@個無線網(wǎng)絡(luò)傳輸系統(tǒng),本文研究了遙感圖像去噪過程和遙感圖像分類過程,將分類后的遙感圖像通過本系統(tǒng)進行傳輸,實現(xiàn)了遙感圖像分類傳輸系統(tǒng)。本文的主要研究內(nèi)容包括以下四個方面:1)無線網(wǎng)絡(luò)傳輸系統(tǒng)中業(yè)務(wù)平臺的設(shè)計與實現(xiàn),無線平臺和業(yè)務(wù)平臺間的通信協(xié)議SWIP協(xié)議的設(shè)計,無線平臺之間信息傳輸?shù)膶崿F(xiàn)與傳輸過程的說明。2)遙感圖像包含的噪聲類型分析,針對遙感圖像中包含的噪聲類型,選取了中值濾波和小波閾值去噪法進行去噪處理,分析了傳統(tǒng)小波閾值去噪法存在的不足,提出了一種雙閾值小波閾值去噪函數(shù)。3)分析并比較常用的圖像分類算法,選取K均值聚類算法對遙感圖像進行分類,針對傳統(tǒng)K均值聚類算法在遙感圖像分類過程中存在的問題,提出了一種自適應(yīng)確定分類數(shù)并優(yōu)化初始聚類中心的K均值聚類算法。4)無線網(wǎng)絡(luò)傳輸系統(tǒng)應(yīng)用于遙感圖像分類中,實現(xiàn)了遙感圖像分類傳輸系統(tǒng)。本文通過Matlab仿真實驗,將峰值信噪比作為圖像去噪效果的客觀評價標準,對比了傳統(tǒng)小波闞值去噪算法與改進的小波閾值去噪算法的去噪效果,實驗表明改進的小波閾值去噪法對遙感圖像去噪效果更佳。同樣的,通過對比實驗發(fā)現(xiàn),改進的K均值聚類算法對遙感圖像的分類效果更佳。
[Abstract]:In order to ensure that the information can be transmitted quickly without limiting the network, signal, security and other factors, we have designed and developed a wireless network transmission system in cooperation with the military. This system transmits encrypted information through FPGA radio frequency signal. Without interference from network, signal, security and other factors, not only can normal communication be carried out, but also can be used for field rescue. The current system is mainly composed of two parts: service platform and wireless platform. Based on this wireless network transmission system, the process of remote sensing image denoising and remote sensing image classification is studied in this paper. The classified remote sensing image is transmitted through this system, and the remote sensing image classification transmission system is realized. The main research contents of this paper include the following four aspects: 1) the design and implementation of the service platform in the wireless network transmission system. The design of communication protocol SWIP protocol between wireless platform and service platform, the realization of information transmission between wireless platforms and the description of transmission process. 2) the noise type analysis of remote sensing image, aiming at the noise type included in remote sensing image. The median filter and wavelet threshold denoising method are selected for denoising processing. The shortcomings of traditional wavelet threshold denoising method are analyzed, and a double threshold wavelet threshold denoising function .3) is proposed to analyze and compare the common image classification algorithm. The K-means clustering algorithm is selected to classify remote sensing images, and the problems existing in the traditional K-means clustering algorithm in the process of remote sensing image classification are pointed out. This paper presents a K-means clustering algorithm. 4) the wireless network transmission system is applied to remote sensing image classification. The remote sensing image classification and transmission system is realized. In this paper, the Matlab simulation experiment is carried out. The peak signal-to-noise ratio (PSNR) is taken as the objective evaluation criterion of image denoising effect, and the denoising effect of traditional wavelet threshold de-noising algorithm and improved wavelet threshold de-noising algorithm is compared. The experimental results show that the improved wavelet threshold denoising method is better for remote sensing image denoising. Similarly, it is found that the improved K-means clustering algorithm is better for the classification of remote sensing images.
【學位授予單位】：北京郵電大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP751

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