Abstract
In an earlier publication we reported on the effectiveness of the Burrows-Wheeler transformation followed by inversion coder (BWIC) in the lossless compression of DNA microarray images where we obtained gains of average 6.5% over generic image compressors. In this work, we propose an enhancement of our previous technique by exploiting the bit distribution of images. Using a simple statistical test, we first decide if it will be gainful to split a 16-bit microarray image into two 8-bit images. In case of splitting, it turns out that the first 8-bit image is highly compressible and we use BWIC to compress it. The second 8-bit image most often contains noise and the bit distribution can become nearly random. We use the Wald-Wolfowitz runs test of randomness to decide whether to compress the second 8-bit image with BWIC or not at all since attempting to compress random data usually results in a larger file size. On select microarray images, by splitting a 16-bit microarray image into 8-bit pieces and selectively compressing the pieces with BWIC, we can achieve upward of 3% compression gain over our previous work.
| Original language | English (US) |
|---|---|
| Title of host publication | 2017 14th International Conference on Smart Cities |
| Subtitle of host publication | Improving Quality of Life Using ICT and IoT, HONET-ICT 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 53-56 |
| Number of pages | 4 |
| Volume | 2017-January |
| ISBN (Electronic) | 9781538607596 |
| DOIs | |
| State | Published - Nov 8 2017 |
| Event | 14th IEEE International Conference on Smart Cities: Improving Quality of Life Using ICT and IoT, HONET-ICT 2017 - Irbid/Amman, Jordan Duration: Oct 9 2017 → Oct 11 2017 |
Other
| Other | 14th IEEE International Conference on Smart Cities: Improving Quality of Life Using ICT and IoT, HONET-ICT 2017 |
|---|---|
| Country | Jordan |
| City | Irbid/Amman |
| Period | 10/9/17 → 10/11/17 |
Fingerprint
Keywords
- BWIC
- DNA Microarray Images
- Inversion Ranks
- Lossless Compression
- Randomness
- Splitting bits
- Wald-Wolfowitz Runs Test
ASJC Scopus subject areas
- Information Systems and Management
- Safety, Risk, Reliability and Quality
- Safety Research
- Artificial Intelligence
- Computer Networks and Communications
- Urban Studies
Cite this
Splitting bits for lossless compression of microarray images. / Koc, Basar; Arnavut, Ziya; Sarkar, Dilip; Kocak, Huseyin.
2017 14th International Conference on Smart Cities: Improving Quality of Life Using ICT and IoT, HONET-ICT 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 53-56.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Splitting bits for lossless compression of microarray images
AU - Koc, Basar
AU - Arnavut, Ziya
AU - Sarkar, Dilip
AU - Kocak, Huseyin
PY - 2017/11/8
Y1 - 2017/11/8
N2 - In an earlier publication we reported on the effectiveness of the Burrows-Wheeler transformation followed by inversion coder (BWIC) in the lossless compression of DNA microarray images where we obtained gains of average 6.5% over generic image compressors. In this work, we propose an enhancement of our previous technique by exploiting the bit distribution of images. Using a simple statistical test, we first decide if it will be gainful to split a 16-bit microarray image into two 8-bit images. In case of splitting, it turns out that the first 8-bit image is highly compressible and we use BWIC to compress it. The second 8-bit image most often contains noise and the bit distribution can become nearly random. We use the Wald-Wolfowitz runs test of randomness to decide whether to compress the second 8-bit image with BWIC or not at all since attempting to compress random data usually results in a larger file size. On select microarray images, by splitting a 16-bit microarray image into 8-bit pieces and selectively compressing the pieces with BWIC, we can achieve upward of 3% compression gain over our previous work.
AB - In an earlier publication we reported on the effectiveness of the Burrows-Wheeler transformation followed by inversion coder (BWIC) in the lossless compression of DNA microarray images where we obtained gains of average 6.5% over generic image compressors. In this work, we propose an enhancement of our previous technique by exploiting the bit distribution of images. Using a simple statistical test, we first decide if it will be gainful to split a 16-bit microarray image into two 8-bit images. In case of splitting, it turns out that the first 8-bit image is highly compressible and we use BWIC to compress it. The second 8-bit image most often contains noise and the bit distribution can become nearly random. We use the Wald-Wolfowitz runs test of randomness to decide whether to compress the second 8-bit image with BWIC or not at all since attempting to compress random data usually results in a larger file size. On select microarray images, by splitting a 16-bit microarray image into 8-bit pieces and selectively compressing the pieces with BWIC, we can achieve upward of 3% compression gain over our previous work.
KW - BWIC
KW - DNA Microarray Images
KW - Inversion Ranks
KW - Lossless Compression
KW - Randomness
KW - Splitting bits
KW - Wald-Wolfowitz Runs Test
UR - http://www.scopus.com/inward/record.url?scp=85043457365&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85043457365&partnerID=8YFLogxK
U2 - 10.1109/HONET.2017.8102221
DO - 10.1109/HONET.2017.8102221
M3 - Conference contribution
VL - 2017-January
SP - 53
EP - 56
BT - 2017 14th International Conference on Smart Cities
PB - Institute of Electrical and Electronics Engineers Inc.
ER -