A 3D Image Quality Assessment Method Based on Vector Information and SVD of Quaternion Matrix under Cloud Computing Environment

Liu, Xingang; Zhang, Lan; Lu, Kaixuan

doi:10.1109/tcc.2015.2513397

Cited by 9 publications

(6 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on MLS spherical surfaces, the fitting implementations such as Guennebaud [ 21 ] use multiple levels of points to represent surfaces. Compared with the method proposed by Fleishman, this method is more stable at low sampling rate and high curvature.…”

Section: Depth Map-based Methodsmentioning

confidence: 99%

Medical Cloud Computing Data Processing to Optimize the Effect of Drugs

2021

Journal of Healthcare Engineering

View full text Add to dashboard Cite

In recent years, cloud computing technology is maturing in the process of growing. Hadoop originated from Apache Nutch and is an open-source cloud computing platform. Moreover, the platform is characterized by large scale, virtualization, strong stability, strong versatility, and support for scalability. It is necessary and far-reaching, based on the characteristics of unstructured medical images, to combine content-based medical image retrieval with the Hadoop cloud platform to conduct research. This study combines the impact mechanism of senile dementia vascular endothelial cells with cloud computing to construct a corresponding data retrieval platform of the cloud computing image set. Moreover, this study uses Hadoop’s core framework distributed file system HDFS to upload images, store the images in the HDFS and image feature vectors in HBase, and use MapReduce programming mode to perform parallel retrieval, and each of the nodes cooperates with each other. The results show that the proposed method has certain effects and can be applied to medical research.

show abstract

Section: Depth Map-based Methodsmentioning

confidence: 99%

Medical Cloud Computing Data Processing to Optimize the Effect of Drugs

2021

Journal of Healthcare Engineering

View full text Add to dashboard Cite

show abstract

“…Liu et al [46] proposed a FR SIQA metric by simulating binocular behaviors of HVS. In [47], Liu et al [46] proposed a novel FR SIQA metric by considering the depth information and integral color information of 3D image under cloud computing environment. Galkandage et al [48] designed a stereoscopic video quality index based on the motion sensitive HVS model.…”

Section: B Siqa Methods Developed By Simulating the Characteristics Of Hvsmentioning

confidence: 99%

Reduced-Reference Stereoscopic Image Quality Assessment Using Gradient Sparse Representation and Structural Degradation

Han

2021

IEEE Access

View full text Add to dashboard Cite

“…, I 16 }. Then we use Otsu algorithm [24], [25] singular value decomposition (SVD) [26], [27] to extract the eigenvalues of I edge . After evaluating the eigenvalues of the I edge , we use Otsu algorithm to divide the eigenvalues into 2 groups and obtain the threshold values, denoted as th svd = [th svd,1 , th svd,2 , .…”

Section: B Prediction Stagementioning

confidence: 99%

Blind Stereoscopic Image Quality Assessment Based on Hierarchical Learning

et al. 2019

View full text Add to dashboard Cite

We proposed a blind image quality assessment model which used classification and prediction for three-dimensional (3D) image quality assessment (denoted as CAP-3DIQA) that can automatically evaluate the quality of stereoscopic images. First, in the classification stage, the model separated the distorted images into several subsets according to the types of image distortions. This process will assign the images with the same distortion type to the same group. After the classification stage, the classified distorted image set is fed into the image quality predictor that contains five different perceptual channels which predict the image quality score individually. Finally, we used the regression module of the support vector machine to evaluate the final image quality score, where the input of the regression model is the combination of five channel's outputs. The model, we proposed is tested on three public and popular databases, which are LIVE 3D Image Quality Database Phase I, LIVE 3D Image Quality Database Phase II, and MCL 3D Image Quality Database. The experimental results show that our proposed model leads to significant performance improvement on quality prediction for stereoscopic images compared with other existing state-of-the-art quality metrics.INDEX TERMS Hierarchical learning, image quality assessment, no reference, stereoscopic images.

show abstract

A 3D Image Quality Assessment Method Based on Vector Information and SVD of Quaternion Matrix under Cloud Computing Environment

Cited by 9 publications

References 29 publications

Medical Cloud Computing Data Processing to Optimize the Effect of Drugs

Medical Cloud Computing Data Processing to Optimize the Effect of Drugs

Reduced-Reference Stereoscopic Image Quality Assessment Using Gradient Sparse Representation and Structural Degradation

Blind Stereoscopic Image Quality Assessment Based on Hierarchical Learning

Contact Info

Product

Resources

About