TY - GEN
T1 - Human visual system inspired color space transform in lossy JPEG 2000 and JPEG XR Compression
AU - Starosolski, Roman
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - In this paper, we present a very simple color space transform HVSCT inspired by an actual analog transform performed by the human visual system. We evaluate the applicability of the transform to lossy image compression by comparing it, in the cases of JPEG 2000 and JPEG-XR coding, to the ICT/YCbCr and YCoCg transforms for 3 sets of test images. The presented transform is competitive, especially for high-quality or near-lossless compression. In general, while the HVSCT transform results in PSNR close to YCoCg and better than the most commonly used YCbCr transform, at the highest bitrates it is in many cases the best among the tested transforms. The HVSCT applicability reaches beyond the compressed image storage; as its components are closer to the components transmitted to the human brain via the optic nerve than the components of traditional transforms, it may be effective for algorithms aimed at mimicking the effects of processing done by the human visual system, e.g., for image recognition, retrieval, or image analysis for data mining.
AB - In this paper, we present a very simple color space transform HVSCT inspired by an actual analog transform performed by the human visual system. We evaluate the applicability of the transform to lossy image compression by comparing it, in the cases of JPEG 2000 and JPEG-XR coding, to the ICT/YCbCr and YCoCg transforms for 3 sets of test images. The presented transform is competitive, especially for high-quality or near-lossless compression. In general, while the HVSCT transform results in PSNR close to YCoCg and better than the most commonly used YCbCr transform, at the highest bitrates it is in many cases the best among the tested transforms. The HVSCT applicability reaches beyond the compressed image storage; as its components are closer to the components transmitted to the human brain via the optic nerve than the components of traditional transforms, it may be effective for algorithms aimed at mimicking the effects of processing done by the human visual system, e.g., for image recognition, retrieval, or image analysis for data mining.
KW - Bio-inspired computations
KW - Color space transform
KW - Human visual system
KW - ICT
KW - Image compression standards
KW - Image processing
KW - JPEG 2000
KW - JPEG XR
KW - LDgEb
KW - Lossy image compression
KW - YCbCr
KW - YCoCg
UR - https://www.scopus.com/pages/publications/85019688361
U2 - 10.1007/978-3-319-58274-0_44
DO - 10.1007/978-3-319-58274-0_44
M3 - Conference contribution
AN - SCOPUS:85019688361
SN - 9783319582733
T3 - Communications in Computer and Information Science
SP - 564
EP - 575
BT - Beyond Databases, Architectures and Structures
A2 - Kozielski, Stanislaw
A2 - Mrozek, Dariusz
A2 - Kasprowski, Pawel
A2 - Malysiak-Mrozek, Bozena
A2 - Kostrzewa, Daniel
PB - Springer Verlag
T2 - 13th International Conference on Beyond Databases, Architectures and Structures, BDAS 2017
Y2 - 30 May 2017 through 2 June 2017
ER -