本文關鍵詞： 圖像質量評價 人類視覺系統(tǒng) 屏幕圖像 梯度方向 邊緣模型　出處：《華僑大學》2017年碩士論文　論文類型：學位論文

【摘要】：隨著移動互聯(lián)網(wǎng)、云計算以及物聯(lián)網(wǎng)等技術的快速發(fā)展,屏幕圖像獲得了越來越多的關注和應用。與自然圖像不同,屏幕圖像既包含由計算機直接生成或渲染的非連續(xù)色調內容,如文字、圖表和圖形等,又含有由攝像機采集得到的連續(xù)色調內容,如自然場景圖片和視頻片段等。屏幕圖像在獲取、存儲、編碼、傳輸和顯示過程中會不可避免地引入各種類型的失真從而導致圖像視覺效果降低。因此,如何準確評價屏幕圖像質量是屏幕圖像技術領域一個至關重要的問題�，F(xiàn)有的大部分圖像質量評價算法和圖像質量評價數(shù)據(jù)庫都是針對自然圖像而設計的,由于屏幕圖像與自然圖像的不同統(tǒng)計特性,他們并不能完全適用于屏幕圖像。因此,本篇論文根據(jù)人眼視覺特征和屏幕圖像特點系統(tǒng)探索了屏幕圖像質量評價方法,包括基于梯度方向的屏幕圖像質量評價方法、基于邊緣模型的屏幕圖像質量評價方法、通用屏幕圖像質量評價數(shù)據(jù)庫。具體如下:1、在分析了屏幕圖像與自然圖像梯度幅值的顯著差異和梯度方向與人類視覺系統(tǒng)相關性的基礎上,設計了一種基于梯度方向的全參考型屏幕圖像質量評價算法。該算法首先提出一種能夠有效捕獲屏幕圖像失真特性的梯度方向計算方法,然后計算參考和失真屏幕圖像的梯度方向相似度,進而融合梯度幅值相似度以獲得最終的失真屏幕圖像質量指標。實驗結果表明,提出的方法能夠有效準確地評價屏幕圖像感知質量。2、考慮到人眼視覺對于圖像邊緣比較敏感且屏幕圖像含有大量邊緣,提出了一種基于參數(shù)化邊緣模型的全參考型屏幕圖像質量評價方法。該方法首先通過邊緣模型分別從參考和失真屏幕圖像中提取兩種顯著的邊緣屬性:邊緣對比度和邊緣寬度,然后分別計算參考和失真屏幕圖像的邊緣對比度相似度和邊緣寬度相似度,最后使用基于邊緣寬度的權重合并方法計算失真屏幕圖像質量評價分數(shù)。實驗結果證明,所提方法與人類視覺系統(tǒng)對屏幕圖像的主觀感知一致性較好。3、考慮到現(xiàn)有的最大屏幕圖像質量評價數(shù)據(jù)庫存在參考圖像和失真類型不夠全面的問題,建立了一個目前最大的主觀屏幕圖像質量評價數(shù)據(jù)庫SCID。根據(jù)屏幕圖像和其實際應用場景特點選取了40張參考屏幕圖像,并使用9種常見的失真類型生成1800張失真屏幕圖像。嚴格遵照國際標準采用雙刺激損傷測量法獲取失真屏幕圖像的主觀質量評分,經(jīng)過分析與處理后得到每張失真屏幕圖像的MOS值作為感知質量的真實值�；谒鶚嫿ǖ腟CID,我們深入評估了13種具有代表性的客觀圖像質量評價模型,并進行了詳盡分析。該數(shù)據(jù)庫將通過開放共享作為屏幕圖像領域的一個重要數(shù)據(jù)庫,對促進屏幕圖像技術領域的研究工作具有重要意義。綜上所述,本文主要根據(jù)屏幕圖像特點和人眼視覺特性分析與探索屏幕圖像質量評價方法,具有一定的創(chuàng)新性和挑戰(zhàn)性。本文的研究成果在一定程度上為基于人類視覺系統(tǒng)的屏幕圖像技術開拓了視野,具有重要的理論研究意義和實際應用價值。
[Abstract]:With the rapid development of mobile Internet, cloud computing and networking technologies, the screen image gained more and more attention. Different from the natural image, non continuous tone, the screen image contains not only directly generated by the computer or rendering such as text, graphics and graphics, but also contains the content of continuous tone collected by the camera the natural scene, such as pictures and video clips. The screen image acquisition, storage, encoding, transmission and display process will inevitably introduce various types of distortion resulting image visual effect is reduced. Therefore, how to accurately evaluate the screen image quality is one of the most important technology in the field of screen image and image evaluation algorithm. The quality of most of the image quality evaluation is based on the existing database of natural images and design, because the screen images and natural images with different statistical characteristics And they are not fully suitable for the screen image. Therefore, this thesis explores the image quality evaluation method based on human visual characteristics of the screen and the screen image features of the system, including the screen image quality evaluation method based on the gradient direction, quality evaluation method of edge model based on screen image, general screen image quality evaluation database as follows. 1, based on the analysis of the significant differences between the screen image and natural image gradient amplitude and gradient direction and the correlation of the human visual system, an algorithm of full reference image quality assessment screen based on gradient direction design. The algorithm first proposed can effectively capture a screen image distortion gradient direction calculation method. Then calculate the gradient direction similarity reference and the distortion of screen image, and then the fusion gradient amplitude similarity in order to get lost really the final screen The image quality index. The experimental results show that the proposed method can effectively and accurately evaluate the perceived quality of the screen image of.2, taking into account the human visual system for image edge sensitive and the screen image contains a large number of edges, presents a screen full reference image quality assessment based on parametric edge model method. This method firstly edge model respectively. From the reference and distortion from two significant attributes: the width of the screen image edge edge contrast and edge, and then calculate the width of edge contrast similarity and edge similarity reference and distortion of the screen image, finally use the distortion of image quality evaluation score screen to calculate the weight combination method based on the width of the edge. The experimental results show that the proposed method with the human visual system to screen image perceived consistent.3, taking into account the existing maximum screen image quality The evaluation database has the reference image and the distortion type is not comprehensive, set up a current evaluation of subjective image quality database SCID. the largest screen according to the screen image and its application scene features selected 40 a reference screen image, and use the 9 common types of distortion generated 1800 distortion screen image in strict accordance with international standards. Double stimulation damage measurement method to obtain the subjective quality score distortion of the screen image, after analysis and processing after each screen image distortion MOS value as the perceived quality of the true value. The construction of SCID based on our in-depth evaluation of the 13 kinds of objective image quality evaluation of representative models, and analyzes in detail the. The database will share an important database as the screen image field through the open, is to promote the research work of the technical field of the screen image Important. To sum up, this paper mainly based on the analysis and exploration of image quality evaluation method of screen screen image features and features of human vision, with innovative and challenging. The research results of this paper to a certain extent for the screen images of the human visual system to develop a vision based research has important theoretical significance and practical application value.

【學位授予單位】：華僑大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP391.41

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