On the statistics of natural stochastic textures and their application in image processing

Statistics of natural images has become an important subject of research in recent years. The highly kurtotic, non-Gaussian, statistics known to be characteristic of many natural images are exploited in various image processing tasks. In this paper, we focus on natural stochastic textures (NST) and...

Full description

Saved in:
Bibliographic Details
Main Authors: Zachevsky, Ido, Zeevi, Yehoshua Y.
Format: Conference Proceeding
Language:English
Subjects:
denoising
fractional Brownian motion
Gaussian distribution
Image resolution
Image texture enhancement
natural image statistics
Noise reduction
PSNR
self-similarity
Signal resolution
Stochastic processes
superresolution
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 5833
container_issue
container_start_page 5829
container_title
container_volume
creator Zachevsky, Ido
Zeevi, Yehoshua Y.
description Statistics of natural images has become an important subject of research in recent years. The highly kurtotic, non-Gaussian, statistics known to be characteristic of many natural images are exploited in various image processing tasks. In this paper, we focus on natural stochastic textures (NST) and substantiate our finding that NST have Gaussian statistics. Using the well-known statistical self-similarity property of natural images, exhibited even more profoundly in NST, we exploit a Gaussian self-similar process known as the fractional Brownian motion, to derive a fBm-PDE-based singleimage superresolution scheme for textured images. Using the same process as a prior, we also apply it in denoising of NST.
doi_str_mv 10.1109/ICASSP.2014.6854721
format conference_proceeding
fullrecord <record><control><sourceid>ieee_CHZPO</sourceid><recordid>TN_cdi_ieee_primary_6854721</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6854721</ieee_id><sourcerecordid>6854721</sourcerecordid><originalsourceid>FETCH-LOGICAL-i175t-a3b590a6072e4fbb4147758cc96ce536fb07b651d97dd3d689b60443f18aaf953</originalsourceid><addsrcrecordid>eNotkN1KAzEUhKMouNY-QW_yAlvzn5xLKf5BoUIVxJuSZLNtZN1dNhH07U2xcGDggxnODEILSpaUErh9Xt1tty9LRqhYKiOFZvQMzUEbKjQAM8DFOaoY11BTIO8XqKKSkVpRAVfoOqVPQojRwlToY9PjfAg4ZZtjytEnPLS4t_l7sl2hgz_YI8Y5_BQWErZ9c3TECdtx7KIvvqHHsdyX3Qc8ToMPKcV-f4MuW9ulMD_pDL093L-unur15rEUWNeRaplry50EYhXRLIjWOVE6aGm8B-WD5Kp1RDslaQO6aXijDDhFhOAtNda2IPkMLf5zYwhhN07lj-l3d5qF_wHRgFZp</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>On the statistics of natural stochastic textures and their application in image processing</title><source>IEEE Xplore All Conference Series</source><creator>Zachevsky, Ido ; Zeevi, Yehoshua Y.</creator><creatorcontrib>Zachevsky, Ido ; Zeevi, Yehoshua Y.</creatorcontrib><description>Statistics of natural images has become an important subject of research in recent years. The highly kurtotic, non-Gaussian, statistics known to be characteristic of many natural images are exploited in various image processing tasks. In this paper, we focus on natural stochastic textures (NST) and substantiate our finding that NST have Gaussian statistics. Using the well-known statistical self-similarity property of natural images, exhibited even more profoundly in NST, we exploit a Gaussian self-similar process known as the fractional Brownian motion, to derive a fBm-PDE-based singleimage superresolution scheme for textured images. Using the same process as a prior, we also apply it in denoising of NST.</description><identifier>ISSN: 1520-6149</identifier><identifier>EISSN: 2379-190X</identifier><identifier>EISBN: 9781479928934</identifier><identifier>EISBN: 1479928933</identifier><identifier>DOI: 10.1109/ICASSP.2014.6854721</identifier><language>eng</language><publisher>IEEE</publisher><subject>denoising ; fractional Brownian motion ; Gaussian distribution ; Image resolution ; Image texture enhancement ; natural image statistics ; Noise reduction ; PSNR ; self-similarity ; Signal resolution ; Stochastic processes ; superresolution</subject><ispartof>2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014, p.5829-5833</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6854721$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,777,781,786,787,27906,54536,54913</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6854721$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Zachevsky, Ido</creatorcontrib><creatorcontrib>Zeevi, Yehoshua Y.</creatorcontrib><title>On the statistics of natural stochastic textures and their application in image processing</title><title>2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</title><addtitle>ICASSP</addtitle><description>Statistics of natural images has become an important subject of research in recent years. The highly kurtotic, non-Gaussian, statistics known to be characteristic of many natural images are exploited in various image processing tasks. In this paper, we focus on natural stochastic textures (NST) and substantiate our finding that NST have Gaussian statistics. Using the well-known statistical self-similarity property of natural images, exhibited even more profoundly in NST, we exploit a Gaussian self-similar process known as the fractional Brownian motion, to derive a fBm-PDE-based singleimage superresolution scheme for textured images. Using the same process as a prior, we also apply it in denoising of NST.</description><subject>denoising</subject><subject>fractional Brownian motion</subject><subject>Gaussian distribution</subject><subject>Image resolution</subject><subject>Image texture enhancement</subject><subject>natural image statistics</subject><subject>Noise reduction</subject><subject>PSNR</subject><subject>self-similarity</subject><subject>Signal resolution</subject><subject>Stochastic processes</subject><subject>superresolution</subject><issn>1520-6149</issn><issn>2379-190X</issn><isbn>9781479928934</isbn><isbn>1479928933</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2014</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotkN1KAzEUhKMouNY-QW_yAlvzn5xLKf5BoUIVxJuSZLNtZN1dNhH07U2xcGDggxnODEILSpaUErh9Xt1tty9LRqhYKiOFZvQMzUEbKjQAM8DFOaoY11BTIO8XqKKSkVpRAVfoOqVPQojRwlToY9PjfAg4ZZtjytEnPLS4t_l7sl2hgz_YI8Y5_BQWErZ9c3TECdtx7KIvvqHHsdyX3Qc8ToMPKcV-f4MuW9ulMD_pDL093L-unur15rEUWNeRaplry50EYhXRLIjWOVE6aGm8B-WD5Kp1RDslaQO6aXijDDhFhOAtNda2IPkMLf5zYwhhN07lj-l3d5qF_wHRgFZp</recordid><startdate>201405</startdate><enddate>201405</enddate><creator>Zachevsky, Ido</creator><creator>Zeevi, Yehoshua Y.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201405</creationdate><title>On the statistics of natural stochastic textures and their application in image processing</title><author>Zachevsky, Ido ; Zeevi, Yehoshua Y.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-a3b590a6072e4fbb4147758cc96ce536fb07b651d97dd3d689b60443f18aaf953</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2014</creationdate><topic>denoising</topic><topic>fractional Brownian motion</topic><topic>Gaussian distribution</topic><topic>Image resolution</topic><topic>Image texture enhancement</topic><topic>natural image statistics</topic><topic>Noise reduction</topic><topic>PSNR</topic><topic>self-similarity</topic><topic>Signal resolution</topic><topic>Stochastic processes</topic><topic>superresolution</topic><toplevel>online_resources</toplevel><creatorcontrib>Zachevsky, Ido</creatorcontrib><creatorcontrib>Zeevi, Yehoshua Y.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEL</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Zachevsky, Ido</au><au>Zeevi, Yehoshua Y.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>On the statistics of natural stochastic textures and their application in image processing</atitle><btitle>2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</btitle><stitle>ICASSP</stitle><date>2014-05</date><risdate>2014</risdate><spage>5829</spage><epage>5833</epage><pages>5829-5833</pages><issn>1520-6149</issn><eissn>2379-190X</eissn><eisbn>9781479928934</eisbn><eisbn>1479928933</eisbn><abstract>Statistics of natural images has become an important subject of research in recent years. The highly kurtotic, non-Gaussian, statistics known to be characteristic of many natural images are exploited in various image processing tasks. In this paper, we focus on natural stochastic textures (NST) and substantiate our finding that NST have Gaussian statistics. Using the well-known statistical self-similarity property of natural images, exhibited even more profoundly in NST, we exploit a Gaussian self-similar process known as the fractional Brownian motion, to derive a fBm-PDE-based singleimage superresolution scheme for textured images. Using the same process as a prior, we also apply it in denoising of NST.</abstract><pub>IEEE</pub><doi>10.1109/ICASSP.2014.6854721</doi><tpages>5</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISSN: 1520-6149
ispartof 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014, p.5829-5833
issn 1520-6149
2379-190X
language eng
recordid cdi_ieee_primary_6854721
source IEEE Xplore All Conference Series
subjects denoising
fractional Brownian motion
Gaussian distribution
Image resolution
Image texture enhancement
natural image statistics
Noise reduction
PSNR
self-similarity
Signal resolution
Stochastic processes
superresolution
title On the statistics of natural stochastic textures and their application in image processing
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-18T03%3A34%3A16IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_CHZPO&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=On%20the%20statistics%20of%20natural%20stochastic%20textures%20and%20their%20application%20in%20image%20processing&rft.btitle=2014%20IEEE%20International%20Conference%20on%20Acoustics,%20Speech%20and%20Signal%20Processing%20(ICASSP)&rft.au=Zachevsky,%20Ido&rft.date=2014-05&rft.spage=5829&rft.epage=5833&rft.pages=5829-5833&rft.issn=1520-6149&rft.eissn=2379-190X&rft_id=info:doi/10.1109/ICASSP.2014.6854721&rft.eisbn=9781479928934&rft.eisbn_list=1479928933&rft_dat=%3Cieee_CHZPO%3E6854721%3C/ieee_CHZPO%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i175t-a3b590a6072e4fbb4147758cc96ce536fb07b651d97dd3d689b60443f18aaf953%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6854721&rfr_iscdi=true