WO2006096162A3 - Method for content driven image compression - Google Patents

Method for content driven image compression Download PDF

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Publication number
WO2006096162A3
WO2006096162A3 PCT/US2005/007009 US2005007009W WO2006096162A3 WO 2006096162 A3 WO2006096162 A3 WO 2006096162A3 US 2005007009 W US2005007009 W US 2005007009W WO 2006096162 A3 WO2006096162 A3 WO 2006096162A3
Authority
WO
WIPO (PCT)
Prior art keywords
data
video
dimensional image
filter
modeling
Prior art date
Application number
PCT/US2005/007009
Other languages
French (fr)
Other versions
WO2006096162A2 (en
Inventor
Jacob Yadegar
Joseph Yadegar
Original Assignee
Jacob Yadegar
Joseph Yadegar
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Jacob Yadegar, Joseph Yadegar filed Critical Jacob Yadegar
Priority to PCT/US2005/007009 priority Critical patent/WO2006096162A2/en
Publication of WO2006096162A2 publication Critical patent/WO2006096162A2/en
Publication of WO2006096162A3 publication Critical patent/WO2006096162A3/en

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/217—Validation; Performance evaluation; Active pattern learning techniques

Abstract

A method with related structures and computational components and modules for modeling data, particularly audio and video signals. The modeling method can be applied to different solutions such as 2-dimensional image/video compression, 3-dimensional image/video compression, 2-dimensional image/video understanding, knowledge discovery and mining, 3-dimensional image/video understanding, knowledge discovery and mining, pattern recognition, object meshing/tessellation, audio compression, audio understanding, etc. Data representing audio or video signals is subject to filtration and modeling by a first filter that tessellates data having a lower dynamic range. A second filter then further tessellates, if needed, and analyzes and models the remaining parts of data, not analyzable by first filter, having a higher dynamic range. A third filter collects in a generally lossless manner the overhead or residual data not modeled by the first and second filters. A variety of techniques including computational geometry, artificial intelligence, machine learning and data mining may be used to better achieve modeling in the first and second filters.
PCT/US2005/007009 2005-03-04 2005-03-04 Method for content driven image compression WO2006096162A2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/US2005/007009 WO2006096162A2 (en) 2005-03-04 2005-03-04 Method for content driven image compression

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/US2005/007009 WO2006096162A2 (en) 2005-03-04 2005-03-04 Method for content driven image compression

Publications (2)

Publication Number Publication Date
WO2006096162A2 WO2006096162A2 (en) 2006-09-14
WO2006096162A3 true WO2006096162A3 (en) 2009-04-02

Family

ID=36953770

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2005/007009 WO2006096162A2 (en) 2005-03-04 2005-03-04 Method for content driven image compression

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WO (1) WO2006096162A2 (en)

Families Citing this family (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
PT3301648T (en) * 2010-04-13 2020-04-20 Ge Video Compression Llc Inheritance in sample array multitree subdivision
US9734436B2 (en) 2015-06-05 2017-08-15 At&T Intellectual Property I, L.P. Hash codes for images
GR20170100133A (en) * 2017-03-30 2018-10-31 Τεχνολογικο Εκπαιδευτικο Ιδρυμα Ανατολικης Μακεδονιας Και Θρακης Method for the education of anthropoid robots
US10650631B2 (en) 2017-07-28 2020-05-12 Hand Held Products, Inc. Systems and methods for processing a distorted image
US11463681B2 (en) 2018-02-23 2022-10-04 Nokia Technologies Oy Encoding and decoding of volumetric video
US10674152B2 (en) * 2018-09-18 2020-06-02 Google Llc Efficient use of quantization parameters in machine-learning models for video coding
CN110046579B (en) * 2019-04-18 2023-04-07 重庆大学 Deep Hash pedestrian re-identification method
US11038528B1 (en) * 2020-06-04 2021-06-15 International Business Machines Corporation Genetic programming based compression determination
CN115937456B (en) * 2023-02-15 2023-05-05 天津市测绘院有限公司 Top layer reconstruction method and reconstruction system for live-action three-dimensional model

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6897977B1 (en) * 2000-11-20 2005-05-24 Hall Aluminum Llc Lossy method for compressing pictures and video

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6897977B1 (en) * 2000-11-20 2005-05-24 Hall Aluminum Llc Lossy method for compressing pictures and video

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
"Digital Signal Processing, 2002, DSP 2002, 2002 14th International Conference", vol. 2, 2002, article TSISHKOU, D. ET AL.: "Mosaic ultrasound medical image compression using TTA10 algorithm.", pages: 1173 - 1177 *
"Electrical & Computer Engineering, 1996, Canadian Conference on 26-29 May 1996", vol. 2, May 1996, article DANSEREAU, R. ET AL.: "Perceptual image compression through fractal surface interpolation.", pages: 899 - 902 *

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Publication number Publication date
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