Noise is the most common type of image distortion affecting human visual perception.In this paper,we propose a no-reference image quality assessment(IQA)method for noisy images incorporating the features of entropy,gr...Noise is the most common type of image distortion affecting human visual perception.In this paper,we propose a no-reference image quality assessment(IQA)method for noisy images incorporating the features of entropy,gradient,and kurtosis.Specifically,image noise estimation is conducted in the discrete cosine transform domain based on skewness invariance.In the principal component analysis domain,kurtosis feature is obtained by statistically counting the significant differences between images with and without noise.In addition,both the consistency between the entropy and kurtosis features and the subjective scores are improved by combining them with the gradient coefficient.Support vector regression is applied to map all extracted features into an integrated scoring system.The proposed method is evaluated in three mainstream databases(i.e.,LIVE,TID2013,and CSIQ),and the results demonstrate the superiority of the proposed method according to the Pearson linear correlation coefficient which is the most significant indicator in IQA.展开更多
The main purpose of this study is to classify the rock mass quality by using rock mass quality (Q) and Rock Mass Rating (RMR) systems along headrace tunnel of small hydropower in Mansehra District, Khyber Pakhtunkhwa....The main purpose of this study is to classify the rock mass quality by using rock mass quality (Q) and Rock Mass Rating (RMR) systems along headrace tunnel of small hydropower in Mansehra District, Khyber Pakhtunkhwa. Geological field work was carried out to determine the orientation, spacing, aperture, roughness and alteration of discontinuities of rock mass. The quality of rock mass along the tunnel route is classified as good to very poor quality by Q system, while very good to very poor by RMR classification system. The relatively good rock conditions are acquired via RMR values that are attributed to ground water conditions, joint spacing, RQD and favorable orientation of discontinuities with respect to the tunnel drive. The petrographic studies revealed that study area is mainly comprised of five major geological rock units namely quartz mica schist (QMS), garnet mica schist (GMS), garnet bearing quartz mica schist (G-QMS), calcareous schist (CS), marble (M). The collected samples of quartz mica schist, marble and garnet bearing quartz mica schist are fine to medium grained, compact and are cross cut by few discontinuities having greater spacing. Therefore, these rocks have greater average RQD, Q values, RMR ratings as compared to garnet mica schist and calcareous schist.展开更多
基金Project supported by the National Natural Science Foundation of China(No.61702332)the Zhejiang Provincial Natural Science Foundation of China(Nos.LZY21F030001 and LSD19H180001)。
文摘Noise is the most common type of image distortion affecting human visual perception.In this paper,we propose a no-reference image quality assessment(IQA)method for noisy images incorporating the features of entropy,gradient,and kurtosis.Specifically,image noise estimation is conducted in the discrete cosine transform domain based on skewness invariance.In the principal component analysis domain,kurtosis feature is obtained by statistically counting the significant differences between images with and without noise.In addition,both the consistency between the entropy and kurtosis features and the subjective scores are improved by combining them with the gradient coefficient.Support vector regression is applied to map all extracted features into an integrated scoring system.The proposed method is evaluated in three mainstream databases(i.e.,LIVE,TID2013,and CSIQ),and the results demonstrate the superiority of the proposed method according to the Pearson linear correlation coefficient which is the most significant indicator in IQA.
文摘The main purpose of this study is to classify the rock mass quality by using rock mass quality (Q) and Rock Mass Rating (RMR) systems along headrace tunnel of small hydropower in Mansehra District, Khyber Pakhtunkhwa. Geological field work was carried out to determine the orientation, spacing, aperture, roughness and alteration of discontinuities of rock mass. The quality of rock mass along the tunnel route is classified as good to very poor quality by Q system, while very good to very poor by RMR classification system. The relatively good rock conditions are acquired via RMR values that are attributed to ground water conditions, joint spacing, RQD and favorable orientation of discontinuities with respect to the tunnel drive. The petrographic studies revealed that study area is mainly comprised of five major geological rock units namely quartz mica schist (QMS), garnet mica schist (GMS), garnet bearing quartz mica schist (G-QMS), calcareous schist (CS), marble (M). The collected samples of quartz mica schist, marble and garnet bearing quartz mica schist are fine to medium grained, compact and are cross cut by few discontinuities having greater spacing. Therefore, these rocks have greater average RQD, Q values, RMR ratings as compared to garnet mica schist and calcareous schist.
