DocumentCode
3149966
Title
Recompressing images to improve image retrieval performance
Author
Edmundson, David ; Schaefer, Gerald
Author_Institution
Dept. of Comput. Sci., Loughborough Univ., Loughborough, UK
fYear
2012
fDate
25-30 March 2012
Firstpage
1541
Lastpage
1544
Abstract
Virtually all images are stored in compressed form, most in (lossy) JPEG format. Compressing images however has been shown to cause a small but not negligible drop in performance for content-based image retrieval (CBIR) algorithms. In this paper, we show that it is possible to reverse this performance drop. We achieve this by what might at a first glance seem counter-intuitive, namely by compressing the images even more. In detail, what we perform is recompressing images (or rather re-quantising the DCT coefficients) to their lowest common image quality setting. We demonstrate, on a benchmark image retrieval database and using standard CBIR algorithms, that this results in improved image retrieval performance rivalling that of running the algorithms on uncompressed data.
Keywords
data compression; discrete cosine transforms; image coding; image retrieval; CBIR algorithms; DCT coefficients; JPEG format; content-based image retrieval algorithms; image quality setting; image recompression; Discrete cosine transforms; Image coding; Image color analysis; Image retrieval; Q factor; Quantization; Transform coding; Content-based image retrieval; JPEG; image compression; retrieval performance;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
Conference_Location
Kyoto
ISSN
1520-6149
Print_ISBN
978-1-4673-0045-2
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2012.6288185
Filename
6288185
Link To Document