TY - GEN
T1 - Near-lossless Image Compression with Parity Reduction
AU - Koc, Basar
AU - Arnavut, Ziya
AU - Voronin, Sergey
AU - Kocak, Huseyin
N1 - Publisher Copyright:
© 2020 IEEE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/7
Y1 - 2020/7
N2 - In our previous work, we introduced a lossless image compression algorithm (called BWIC_I) based on hierarchical prediction, inversion, and context-adaptive coding techniques. We showed that BWIC_I outperformed most commonly used standard color image compression algorithms, including JPEG in lossless mode and JPEG 2000, on a variety of well-known image data sets. In this study, we introduce a near-lossless image compression algorithm that essentially consists of parity reduction by dropping the least significant bit of pixel values of RGB color images and then compressing the resulting data with BWIC_I. The proposed algorithm provides a guaranteed minimum PSNR value. Moreover, it does not require a specialized encoding and decoding algorithm and can be utilized in conjunction with other generic image compression algorithms. The compression performance of the proposed technique is considerably better than JPEG and JPEG 2000, as demonstrated on the standard Kodak image set.
AB - In our previous work, we introduced a lossless image compression algorithm (called BWIC_I) based on hierarchical prediction, inversion, and context-adaptive coding techniques. We showed that BWIC_I outperformed most commonly used standard color image compression algorithms, including JPEG in lossless mode and JPEG 2000, on a variety of well-known image data sets. In this study, we introduce a near-lossless image compression algorithm that essentially consists of parity reduction by dropping the least significant bit of pixel values of RGB color images and then compressing the resulting data with BWIC_I. The proposed algorithm provides a guaranteed minimum PSNR value. Moreover, it does not require a specialized encoding and decoding algorithm and can be utilized in conjunction with other generic image compression algorithms. The compression performance of the proposed technique is considerably better than JPEG and JPEG 2000, as demonstrated on the standard Kodak image set.
KW - BWIC_I
KW - JPEG
KW - JPEG 2000
KW - Least significant bit
KW - Near-lossless image compression
KW - Parity reduction
KW - PSNR
KW - SSIM
UR - http://www.scopus.com/inward/record.url?scp=85092648234&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85092648234&partnerID=8YFLogxK
U2 - 10.1109/INES49302.2020.9147124
DO - 10.1109/INES49302.2020.9147124
M3 - Conference contribution
AN - SCOPUS:85092648234
T3 - INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings
SP - 225
EP - 229
BT - INES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 24th IEEE International Conference on Intelligent Engineering Systems, INES 2020
Y2 - 8 July 2020 through 10 July 2020
ER -