计算机科学与探索
計算機科學與探索
계산궤과학여탐색
JOURNAL OF FRONTIERS OF COMPUTER SCIENCE & TECHNOLOGY
2014年
12期
1517-1524
,共8页
无参考图像质量评价%多核学习%灰度-梯度共生矩阵%结构张量%相位一致
無參攷圖像質量評價%多覈學習%灰度-梯度共生矩陣%結構張量%相位一緻
무삼고도상질량평개%다핵학습%회도-제도공생구진%결구장량%상위일치
non-reference image quality assessment%multiple kernel learning%gray level-gradient co-occurrence matrix%structure tensor%phase congruency
由于多种失真类型灰度-共生矩阵特征的不规则性，单核方法无法取得理想结果，从而提出了一种基于多核学习，针对多种失真类型的无参考图像质量评价方法。首先对灰度图像进行相位一致和结构张量变换，得到相位一致图和结构张量图，然后分别对它们提取灰度-梯度共生矩阵二次统计特征，最后将提取的特征输入到高效的分层多核学习机进行训练学习，预测得到图像的质量评分。多图像库多次随机实验结果表明，新方法结果与主观评价值有较好的一致性，并具有较好的推广性。
由于多種失真類型灰度-共生矩陣特徵的不規則性，單覈方法無法取得理想結果，從而提齣瞭一種基于多覈學習，針對多種失真類型的無參攷圖像質量評價方法。首先對灰度圖像進行相位一緻和結構張量變換，得到相位一緻圖和結構張量圖，然後分彆對它們提取灰度-梯度共生矩陣二次統計特徵，最後將提取的特徵輸入到高效的分層多覈學習機進行訓練學習，預測得到圖像的質量評分。多圖像庫多次隨機實驗結果錶明，新方法結果與主觀評價值有較好的一緻性，併具有較好的推廣性。
유우다충실진류형회도-공생구진특정적불규칙성，단핵방법무법취득이상결과，종이제출료일충기우다핵학습，침대다충실진류형적무삼고도상질량평개방법。수선대회도도상진행상위일치화결구장량변환，득도상위일치도화결구장량도，연후분별대타문제취회도-제도공생구진이차통계특정，최후장제취적특정수입도고효적분층다핵학습궤진행훈련학습，예측득도도상적질량평분。다도상고다차수궤실험결과표명，신방법결과여주관평개치유교호적일치성，병구유교호적추엄성。
Because of the irregular features extracted from images with various types of distortion, the single kernel method cannot get the ideal result, this paper presents a non-reference image quality evaluation method based on multiple kernel learning for various learning types of distortion. Firstly this paper does a conversion of the gray scale image with the structure tensor and the phase congruency, then extracts the secondary statistical features of gray level-gradient co-occurrence matrix from them, finally inputs these features into hierarchical multiple kernel learning machine for training and gets the quality score. The random experiment results on multiple image library show that the new method results are consistent with the subjective evaluation values, and have better generalization.
