Sorry, you need to enable JavaScript to visit this website.

BLIND QUALITY EVALUATOR FOR SCREEN CONTENT IMAGES VIA ANALYSIS OF STRUCTURE

Citation Author(s):
Guanghui Yue, Chunping Hou, and Weisi Lin
Submitted by:
Guanghui Yue
Last updated:
11 May 2019 - 9:48pm
Document Type:
Poster
Document Year:
2019
Event:
Paper Code:
ICASSP19005
Categories:

Abstract 

Abstract: 

Existing blind evaluators for screen content images (SCIs) are mainly learning-based and require a number of training images with co-registered human opinion scores. However, the size of existing databases is small, and it is labor-, timeconsuming and expensive to largely generate human opinion scores. In this study, we propose a novel blind quality evaluator without training. Specifically, the proposed method first calculates the gradient similarity between a distorted image and its translated versions in four directions to estimate the structural distortion, the most obvious distortion in SCIs. Given that the edge region is easier to be distorted, the inter-scale gradient similarity is then calculated as the weighting map. Finally, the proposed method is derived by incorporating the gradient similarity map with the weighting map. Experimental results demonstrate its effectiveness and efficiency on a public available SCI database.

up
0 users have voted:

Dataset Files

icassp 2019 poster 2875.pdf

(247)