本文選題：全參考圖像質(zhì)量評(píng)價(jià) + 區(qū)域級(jí)　； 參考：《北京郵電大學(xué)》2016年碩士論文

【摘要】：隨著科學(xué)技術(shù)的發(fā)展以及互聯(lián)網(wǎng)的普及,數(shù)碼技術(shù)得到了廣泛的應(yīng)用,然而數(shù)字圖像的獲取、處理、編碼、存儲(chǔ)、傳輸和重建這每一個(gè)必要的環(huán)節(jié)都會(huì)影響圖像的質(zhì)量,而圖像質(zhì)量的下降勢必影響到圖像所表達(dá)信息的充分性與準(zhǔn)確性,所以圖像質(zhì)量評(píng)價(jià)顯得尤為重要。圖像處理辦法在不斷改善,高動(dòng)態(tài)范圍圖像的應(yīng)用也越來越廣,圖像評(píng)價(jià)辦法也需要不斷改進(jìn)以適應(yīng)新需求。優(yōu)秀的數(shù)字圖像評(píng)價(jià)方法不僅能夠準(zhǔn)確地反映圖像的質(zhì)量,而且能對(duì)圖像處理技術(shù)提供良好的改進(jìn)方向。本文圍繞全參考圖像質(zhì)量評(píng)價(jià)主題即失真圖像所對(duì)應(yīng)的參考圖像可以獲得,在學(xué)習(xí)和研究已有基于相似性圖像質(zhì)量評(píng)價(jià)的基礎(chǔ)上提出了新的方法。首先,本文在已有一級(jí)加權(quán)策略基礎(chǔ)上提出了二級(jí)加權(quán)方法,對(duì)已有的圖像質(zhì)量評(píng)價(jià)算法進(jìn)行了改進(jìn)。已有的加權(quán)策略都是集中在像素級(jí)的加權(quán)上,而人眼感興趣的往往是某一塊區(qū)域,而不是某一個(gè)像素點(diǎn)。區(qū)域加權(quán)算法具體為:區(qū)域內(nèi)對(duì)像素級(jí)局部質(zhì)量值進(jìn)行加權(quán)得到各個(gè)區(qū)域的質(zhì)量值,區(qū)域間通過各個(gè)區(qū)域的權(quán)重對(duì)區(qū)域間的質(zhì)量值進(jìn)行加權(quán)。其次,人眼是一個(gè)很好的信息提取者。圖像若有失真,人眼從圖像中感受的內(nèi)容信息就會(huì)改變。本文基于人眼的信息提取特性對(duì)圖像的內(nèi)容信息進(jìn)行建模,并結(jié)合梯度和色度特征,提出了一種基于內(nèi)容信息相似性的圖像質(zhì)量評(píng)價(jià)算法。第三,本文融合修正的梯度相似性和圖像的自然性實(shí)現(xiàn)了對(duì)色調(diào)映射圖像的質(zhì)量評(píng)價(jià)。在圖像質(zhì)量評(píng)價(jià)方面公開的數(shù)據(jù)庫上進(jìn)行的試驗(yàn)表明,本文提出的三種算法均取得了良好的性能。
[Abstract]:With the development of science and technology and the popularity of the Internet, digital technology has been widely used. However, the acquisition, processing, coding, storage, transmission and reconstruction of digital images will affect the quality of images. The degradation of image quality is bound to affect the adequacy and accuracy of the information expressed in the image, so it is particularly important to evaluate the image quality. The method of image processing is improving and the application of high dynamic range image is becoming wider and wider. The method of image evaluation also needs to be improved to meet the new needs. Excellent digital image evaluation method can not only accurately reflect the image quality, but also provide a good direction of improvement for image processing technology. In this paper, the reference images corresponding to distorted images can be obtained around the subject of full reference image quality evaluation, and a new method based on similarity image quality evaluation is proposed in this paper. Firstly, based on the existing first-order weighting strategy, a two-level weighting method is proposed to improve the existing image quality evaluation algorithm. The existing weighting strategies are focused on the pixel weighting, and the human eye is always interested in a certain region, not a pixel point. The region weighting algorithm is: the local quality value of each region is weighted in the region, and the quality value of each region is weighted by the weight of each region among the regions. Secondly, the human eye is a good information extractor. If the image is distorted, the content information that the human eye feels from the image will change. In this paper, based on the information extraction characteristics of human eyes, the content information of the image is modeled, and an image quality evaluation algorithm based on the similarity of the content information is proposed by combining the gradient and chromaticity features. Thirdly, this paper combines the modified gradient similarity and the naturalness of the image to evaluate the quality of the hue map image. The experiments on the database of image quality evaluation show that the three algorithms presented in this paper have good performance.
【學(xué)位授予單位】：北京郵電大學(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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本文編號(hào)：2028736