NDLI: Visual Distortion Sensitivity Modeling for Spatially Adaptive Quantization in Remote Sensing Image Compression

Content Provider	IEEE Xplore Digital Library
Author	Yongfei Zhang Haiheng Cao Hongxu Jiang Bo Li
Copyright Year	2004
Abstract	As remote sensing images are often characterized with strong randomness, weak local correlation, and multiple small targets, the commonly used coarse-granularity subband-level quantization scheme fails to make use of these characteristics; thus, the performance improvements of these methods in literature are often marginal. To address this problem, this letter presents a novel spatially adaptive quantization (SAQ) method for the compression of remote sensing images based on our proposed Visual Distortion Sensitivity (ViDiS) Model. The ViDiS model takes into consideration four ViDiS components, including image luminance, spatial frequency, spatial orientation, and visual masking, to help measure the distortion more consistent to the image quality perceived by human beings. Then, a SAQ scheme is proposed to better exploit the content characteristics of remote sensing images, in which the quantization is conducted on a finer subband block level rather than subband level, with the guidance of the ViDiS model. Experimental results show that the proposed algorithm can preserve better visual quality in low-contrast areas with small targets at a competitive computational cost, which makes it more desirable in compression applications for remote sensing images.
Sponsorship	IEEE Geoscience and Remote Sensing Society
Starting Page	723
Ending Page	727
Page Count	5
File Size	586569
File Format	PDF
ISSN	1545598X
Volume Number	11
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Remote sensing Quantization (signal) Image coding Visualization Sensitivity Adaptation models Bit rate visual distortion sensitivity (ViDiS) Human visual system (HVS) quantization remote sensing image compression spatially adaptive
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Geotechnical Engineering and Engineering Geology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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