本文關(guān)鍵詞： 秘密共享 圖像分存 壓縮感知 稀疏變換 信號重構(gòu)　出處：《內(nèi)蒙古大學》2017年碩士論文　論文類型：學位論文

【摘要】：傳統(tǒng)秘密圖像分存技術(shù)需要對圖像的所有數(shù)據(jù)進行處理,由于圖像數(shù)據(jù)量大,所以算法執(zhí)行時間比較長,而且分存算法產(chǎn)生的數(shù)據(jù)總量與原始圖像數(shù)據(jù)量相比擴張明顯,會對網(wǎng)絡(luò)傳輸和存儲造成較大負擔。當圖像信號具有稀疏性,或者在某一種稀疏變換基的表示下絕大部分系數(shù)為零或近似為零時,壓縮感知技術(shù)通過構(gòu)造一個與稀疏基不相關(guān)的適合的測量矩陣對原始圖像進行感知測量。測量得到的數(shù)據(jù)包含了原始圖像的絕大部分有用信息,在確保能夠精確重構(gòu)圖像的同時將原圖像從高維壓縮到低維,極大地減少了需要處理的數(shù)據(jù)量,能很好地解決傳統(tǒng)方法中由于數(shù)據(jù)量大而導(dǎo)致的諸多問題。在信號重構(gòu)端,通過一定的重構(gòu)算法可以獲得原始圖像信息一個精確的或者高度近似的逼近。本文將傳統(tǒng)秘密圖像分存與壓縮感知技術(shù)相結(jié)合,實現(xiàn)了一個基于壓縮感知技術(shù)的秘密圖像分存方案。為了進一步提高方案的性能,又從信號的稀疏表示、信號的感知測量和信號重構(gòu)三個方面對方案進行了優(yōu)化。通過實驗我們發(fā)現(xiàn)本文方案能明顯降低需要處理的數(shù)據(jù)量,有效減少算法執(zhí)行時間,并且重構(gòu)圖像可以達到一個較理想的視覺效果。實驗結(jié)果表明:與經(jīng)典的Thien-Lin方案相比,本文實現(xiàn)的初始方案能平均減少48.66%的圖像分存時間和29.32%的圖像還原時間。優(yōu)化方案可以平均減少58.77%的分存時間和58.16%的還原時間,而且優(yōu)化方案的重構(gòu)圖像精度比初始方案提高了 4-10dB。
[Abstract]:The traditional secret image sharing technology needs to process all the data of the image. Because of the large amount of image data, the execution time of the algorithm is relatively long. Moreover, the total amount of data generated by the split storage algorithm is obviously expanded compared with the original image data volume, which will create a great burden on the network transmission and storage, when the image signal is sparse. Or most of the coefficients are zero or approximately 00:00 under the representation of a sparse transform basis. The compression sensing technique constructs a suitable measurement matrix which is not related to the sparse base to measure the original image. The measured data contain most of the useful information of the original image. At the same time, the original image can be compressed from high dimension to low dimension, which greatly reduces the amount of data to be processed. It can solve many problems caused by large amount of data in traditional methods. A precise or highly approximate approximation of the original image information can be obtained by a certain reconstruction algorithm. In this paper, the traditional secret image sharing and compression sensing techniques are combined. In order to further improve the performance of the scheme, a secret image sharing scheme based on compressed sensing technology is implemented. Through experiments, we find that the proposed scheme can significantly reduce the amount of data to be processed, and effectively reduce the execution time of the algorithm. And the reconstructed image can achieve an ideal visual effect. Experimental results show that: compared with the classical Thien-Lin scheme. The initial scheme in this paper can reduce the average time of image sharing by 48.66% and the time of image restoration by 29.32%. The optimized scheme can reduce the time of sharing by 58.77% and 58.16% on average. The restore time. Moreover, the reconstructed image precision of the optimized scheme is 4-10 dB higher than that of the original scheme.
【學位授予單位】：內(nèi)蒙古大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP391.41

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本文編號：1488258