Photo Album Compression for Cloud Storage Using Local Features

This paper proposes a novel feature-based photo album compression scheme for cloud storage. The main contribution of this paper is the use of local features rather than pixel values for analyzing and exploring the correlation between images. Unlike previously established image set compression scheme...

Full description

Saved in:
Bibliographic Details
Published in:IEEE journal on emerging and selected topics in circuits and systems 2014-03, Vol.4 (1), p.17-28
Main Authors: Shi, Zhongbo, Sun, Xiaoyan, Wu, Feng
Format: Article
Language:English
Subjects:
Cloud computing
Cloud storage
Correlation
Correlation analysis
Deformation
high efficiency video coding (HEVC)
Illumination
Image coding
Image compression
Image edge detection
Lighting
local features
photo album
Redundancy
Robustness
Video compression
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper proposes a novel feature-based photo album compression scheme for cloud storage. The main contribution of this paper is the use of local features rather than pixel values for analyzing and exploring the correlation between images. Unlike previously established image set compression schemes, we adopt content-based feature matching, which is invariant to scale, rotation, and robust to illumination changes, in both correlation estimation and redundancy reduction. Based on feature-based correlation analysis, we organize correlated images as a pseudo sequence by minimizing the predictive cost. Since pseudo sequences have much more complicated correlations than natural videos, we further propose a three-step prediction to reduce inter-image redundancy based on local features. We first propose a feature-based multi-model approach to reduce local geometric deformations between images, resulting in multiple deformed predictions. We then decrease the illumination difference between each deformed prediction and the target image with a photometric transformation. Finally, we reduce redundancy between images using a block-based motion compensation, similar to video compression. Experimental results show that our proposed feature-based coding scheme can be 10 times more efficient than individual JPEG compression.
ISSN:2156-3357
2156-3365
DOI:10.1109/JETCAS.2014.2298291