An Innovative Saliency Guided ROI Selection Model for Panoramic Images Compression

Saliency detection has been an increasingly important tool for ROI selection in image compression. Most previous works on saliency detection are dedicated to conventional images, however, with the rapid development of VR or AR technology, it is becoming more and more important to obtain visual atten...

Full description

Saved in:
Bibliographic Details
Published in2018 Data Compression Conference p. 436
Main Authors Zhu, Chunbiao, Huang, Kan, Li, Ge
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2018
Subjects
Bit rate
Image coding
Panoramic images compression
Predictive models
ROI selection model
Saliency detection
Transform coding
Visualization
Online AccessGet full text

Cover

More Information
Summary:Saliency detection has been an increasingly important tool for ROI selection in image compression. Most previous works on saliency detection are dedicated to conventional images, however, with the rapid development of VR or AR technology, it is becoming more and more important to obtain visual attention for panoramic images. Meanwhile, panoramic images have more potential for improvement in compression performance compared with the conventional case. In this work, we propose an innovative saliency guided ROI selection model. Extensive evaluations show the proposed approach outperforms other methods in saliency accuracy especially for panoramic images. Meanwhile, we improve the compression quality of standard JPEG by using a higher bit rate to encode image regions flagged by our model and lower bit rate elsewhere in the image.
ISSN:2375-0359
DOI:10.1109/DCC.2018.00089