【摘要】：隨著數(shù)字媒體采集、顯示以及處理技術(shù)的飛速發(fā)展,各種高質(zhì)量圖像及視頻的新應(yīng)用和服務(wù)不斷出現(xiàn),使得圖像/視頻數(shù)據(jù)呈爆炸式增長(zhǎng)。海量的圖像/視頻數(shù)據(jù)給傳輸和存儲(chǔ)提出了極高要求,如何實(shí)現(xiàn)高效壓縮已成為圖像及視頻編解碼領(lǐng)域長(zhǎng)期存在的挑戰(zhàn)性問題。近年來,新興的壓縮感知理論大大提高了信號(hào)的壓縮率,降低了信號(hào)存儲(chǔ)和傳輸?shù)膲毫?這對(duì)于圖像及視頻編解碼領(lǐng)域的研究無疑是一個(gè)大的革新和進(jìn)步。本文簡(jiǎn)要介紹了現(xiàn)有的以壓縮感知理論為基礎(chǔ)的圖像編碼算法,重點(diǎn)介紹了分塊壓縮感知理論、稀疏性判定準(zhǔn)則以及利用圖像空間相關(guān)性的自適應(yīng)圖像編碼算法。在此基礎(chǔ)上,本文提出了一種圖像自適應(yīng)編碼算法和兩種針對(duì)圖像序列重構(gòu)的改進(jìn)算法,具體內(nèi)容為:(1)基于壓縮感知的圖像自適應(yīng)編碼算法:本文在滿足編碼端采樣率要求的情況下,根據(jù)圖像塊在TV域的稀疏性,為每一個(gè)圖像塊合理地分配不同的采樣率,以此提高圖像的壓縮率,同時(shí)解碼端也能得到高質(zhì)量的重構(gòu)圖像。(2)基于自適應(yīng)卡爾曼的時(shí)域增強(qiáng)算法:本文在分塊視頻壓縮感知MC-BCS-SPL算法的基礎(chǔ)上,分析了圖像序列中每幅圖像的噪聲分布特征,將自適應(yīng)卡爾曼濾波思想運(yùn)用到圖像序列時(shí)域增強(qiáng)中,對(duì)重構(gòu)后的圖像在時(shí)域方向進(jìn)行濾波,有效去除了幀間噪聲,使圖像的主觀效果有了一定提高。(3)基于TVAL3的圖像序列冗余重構(gòu)算法:本文提出一種將TVAL3及新三步搜索法相結(jié)合的重構(gòu)算法來實(shí)現(xiàn)圖像序列的重構(gòu)。在該算法中將TVAL3算法作為圖像重建的算法,采用新三步搜索法(NTSS)作為塊匹配算法,來得到當(dāng)前幀在參考幀中的最優(yōu)匹配塊。利用上述方法對(duì)圖像序列進(jìn)行重構(gòu)后,需要對(duì)其再進(jìn)行維納濾波,來得到更好的主觀圖像。實(shí)驗(yàn)結(jié)果表明本文提出的基于壓縮感知的自適應(yīng)編碼算法有效減少了編碼端的采樣數(shù)據(jù),實(shí)現(xiàn)了高效壓縮;同時(shí)兩種針對(duì)圖像序列的改進(jìn)重構(gòu)算法也有效提高了圖像序列的重構(gòu)質(zhì)量。
[Abstract]:With the rapid development of digital media acquisition, display and processing technology, a variety of high-quality image and video applications and services continue to appear, resulting in an explosive growth of image / video data. The huge amount of image / video data requires the transmission and storage. How to achieve efficient compression has become a long-standing challenge in the field of image and video coding and decoding. In recent years, the emerging compression sensing theory has greatly improved the compression ratio of signals and reduced the pressure of signal storage and transmission, which is undoubtedly a great innovation and progress in the field of image and video coding and decoding. In this paper, the existing image coding algorithms based on the compression perception theory are briefly introduced, and the block compression perception theory, the sparsity criterion and the adaptive image coding algorithm based on the spatial correlation of the image are emphatically introduced. On this basis, this paper proposes an adaptive image coding algorithm and two improved algorithms for image sequence reconstruction. The main contents are as follows: (1) Image adaptive coding algorithm based on compression perception: in this paper, according to the sparseness of image blocks in TV domain, different sampling rates are reasonably allocated to each image block under the condition that the sampling rate at the coding end is satisfied. In order to improve the compression ratio of the image, high quality reconstructed image can be obtained at the same time. (2) time domain enhancement algorithm based on adaptive Kalman: in this paper, based on the block video compression sensing MC-BCS-SPL algorithm, The noise distribution characteristics of each image in the image sequence are analyzed. The adaptive Kalman filter is applied to the time domain enhancement of the image sequence. The reconstructed image is filtered in the time domain direction, and the inter-frame noise is effectively removed. The subjective effect of image is improved. (3) redundant reconstruction algorithm of image sequence based on TVAL3: in this paper, a reconstruction algorithm combining TVAL3 and new three-step search method is proposed to realize the reconstruction of image sequence. In this algorithm, the TVAL3 algorithm is used as the image reconstruction algorithm, and the new three-step search method (NTSS) is used as the block matching algorithm to obtain the optimal matching block of the current frame in the reference frame. In order to obtain better subjective image, Wiener filtering is needed to reconstruct the image sequence using the above methods. The experimental results show that the proposed adaptive coding algorithm based on compression sensing can effectively reduce the sampling data at the coding end and achieve efficient compression. At the same time, two improved reconstruction algorithms for image sequences also effectively improve the reconstruction quality of image sequences.
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP391.41

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