Paper Info
Title
Human Visual System Inspired Color Space Transform in Lossy JPEG 2000 and JPEG XR Compression.
Abstract
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.
Year
DOI
Venue
2017
10.1007/978-3-319-58274-0_44
Communications in Computer and Information Science
Keywords
Field
DocType
Image processing,Color space transform,Human visual system,Bio-inspired computations,Lossy image compression,ICT,YCbCr,YCoCg,LDgEb,Image compression standards,JPEG 2000,JPEG XR
Computer vision,Lossless JPEG,Lossy compression,Compression artifact,Human visual system model,Computer science,Transform coding,JPEG,Artificial intelligence,Quantization (image processing),JPEG 2000
Conference
Volume
ISSN
Citations 
716
1865-0929
1
PageRank 
References 
Authors
0.38
10
1
Name
Order
Citations
PageRank
Roman Starosolski1397.30