|Table of Contents|

No Reference Quality Assessment for ScreenContent Image Based on SVR(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2021年01期
Page:
57-63
Research Field:
计算机科学与技术
Publishing date:

Info

Title:
No Reference Quality Assessment for ScreenContent Image Based on SVR
Author(s):
Tong Bing
School of Information Engineering,Zhangzhou Institute of Technology,Zhangzhou 363000,China
Keywords:
screen content image; no reference quality assessment; support vector regression; edge feature; luminance feature
PACS:
TP391
DOI:
10.3969/j.issn.1672-1292.2021.01.009
Abstract:
The paper presents a new no reference quality assessment algorithm for screen content image based on support vector regression. Firstly,we calculate the edge map through the difference of Gaussians,which is further used to extract edge features. Secondly,we obtain the luminance map through the local normalization,which is further used to compute luminance features. Finally,we map the quality-aware features to subjective scores through the support vector regression algorithm. Experimental results on two data sets show that the performance of the proposed algorithm is better than those of the most of the existing algorithms.

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Last Update: 2021-03-15