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Dr. Margaret Varga. Defence Evaluation & Research Agency Malvern Worcestershire WR14 3PS UK. Image Processing and Interpretation. Click to add sub-title. Telephone: +44 1684 895712 Facsimile: +44 1684 894384 Email: [email protected] Content Based Compression.

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Content based compression l.jpg

Dr. Margaret Varga

Defence Evaluation

& Research Agency

Malvern

Worcestershire

WR14 3PS

UK

Image Processing and

Interpretation

Click to add sub-title

Telephone: +44 1684 895712

Facsimile: +44 1684 894384

Email: [email protected]

Content Based Compression


Introduction l.jpg
Introduction

  • Huge volumes of images, video are collected:

    • e.g. Infra-red, optical, SAR, sonar, military exercise log book

  • and used:

    • surveillance, monitoring, mission assessment

  • Different characteristics: scale, textural, resolution etc.

  • Require large storage or efficient transmission

  • Need for fast, cost effective and reliable transmission, storage and retrieval


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Current Image Compression Techniques

Problems

  • Only concern with compression ratio

  • Do not address the problems:

    • preserving relevant information

    • removing redundant data

  • Assessing such decompressed images, e.g. ATR -> unpredictable results

  • Lossless still used - images that required detail analysis and/or further processing


Preservation of information l.jpg
Preservation of Information

  • In some applications

  • Local detail is crucial

  • Can not be coded away without changing the meaning and significance of the image

    • Small targets in surveillance imagery

    • Military activity assessment

    • Mission assessment

    • …...


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Cueing Process

  • Cueing - target detection and motion tracking

  • Maximise the detection of:

    • 'True +', i.e. real targets for which lossless (or near lossless) compression must be used;

    • 'True - ', i.e. real redundant areas for which lossy compression can be used;

    • Based on the photographic interpreters’ and intelligence analysts’ annotations

  • Minimise:

    • all the 'False +' and 'False -' , i.e. mistaken targets and background

  • Provide essential and reliable guidance for the application:

    • lossless compression techniques intelligently on the regions/targets of interests

    • lossy compression techniques non-relevant or background areas


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Cueing Process

Still Imagery

  • Manual Annotation

  • Quadtree Based Cueing

  • Phase Congruency

Video

  • Motion Surveillance


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Image Fusion

Under-exposed

Over-exposed

Fused


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Image Fusion

Raw Optical

Raw SAR

Fused


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Manual Annotation

  • Simple and could easily be performed using some form of a graphical user interface (GUI)

  • Form part of a system in which an intelligence analysts or photographic interpreter:

    • could interactively annotate imagery to mark out ROI

    • then being compressed intelligently prior to dispatch


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Manual Annotation

An outline drawn around one particular area of interest in an image


Quadtree l.jpg
Quadtree

  • The Quadtree has been used in compression for many years

  • Its use for target detection is novel

  • The technique consists of decomposing an image into sub-images based on some criteria:

    • grey level similarity, image mean, variance etc.

  • If a region of an image:

    • is described satisfactorily by the chosen criteria then that region is left unmodified

    • otherwise it is decomposed into 4 sub-regions each of equal size.

  • The process continues until

    • no further decomposition is carried out or

    • some minimum region size has been reached



Quadtree13 l.jpg
Quadtree

Standard quadtree HV quatree

The HV-quadtree gives an improved representation of an image yielding in some case up to 75% less regions.

The fine resolution areas of the grid form the masks for ROI


Phase congruency l.jpg
Phase Congruency

  • All image features have in common in the Fourier domain frequency components over a wide range - maximal in phase congruency

  • The angle at which this phase-congruency occurs is characteristic of the type of feature

  • For example:

    • +ve step = 0

    • -ve step = 

    • +ve ridge = /2

    • -ve ridge = 3/2

  • A feature could be defined as the location at which there is a congruence of phase

  • It is invariant to contrast in a feature


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Phase Congruency

The antennae together with their shadows particularly those in the distance are clearly extracted.


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Model Based Motion Tracking

  • Automatic recognition and tracking of vehicles in video sequences from fixed surveillance cameras

  • The technique:

    • fitting 2-D vehicle models to images

    • and then track the movement of the vehicles

    • Uses the Minimum Description Length MDL for model selection

    • can be linked with compression

  • Applications:

    • detecting,

    • tracking and

    • compressing surveillance imagery



Quadtree18 l.jpg
Quadtree

Standard quadtree HV quatree

The HV-quadtree gives an improved representation of an image yielding in some case up to 75% less regions.

The fine resolution areas of the grid form the masks for ROI


Phase congruency19 l.jpg
Phase Congruency

  • All image features have in common in the Fourier domain frequency components over a wide range - maximal in phase congruency

  • The angle at which this phase-congruency occurs is characteristic of the type of feature

  • For example:

    • +ve step = 0

    • -ve step = 

    • +ve ridge = /2

    • -ve ridge = 3/2

  • A feature could be defined as the location at which there is a congruence of phase

  • It is invariant to contrast in a feature


Phase congruency20 l.jpg
Phase Congruency

The antennae together with their shadows particularly those in the distance are clearly extracted.


Model based motion tracking21 l.jpg
Model Based Motion Tracking

  • Automatic recognition and tracking of vehicles in video sequences from fixed surveillance cameras

  • The technique:

    • fitting 2-D vehicle models to images

    • and then track the movement of the vehicles

    • Uses the Minimum Description Length MDL for model selection

    • can be linked with compression

  • Applications:

    • detecting,

    • tracking and

    • compressing surveillance imagery


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MPEG4

RAW Extracted Target Extracted + background

187 frames - small boat in the foreground 800:1



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Performance Evaluation

  • Performance evaluation is important

  • Suitable metrication methods must be identified and implemented

  • Evaluation is a complex and many sided issue


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Target Detection Performance

  • The performance of the target detection process - Receiver Operating Characteristic (ROC)

    • % of true + detection of real targets/regions of interests

    • % of false - detection of target areas as background.

  • The targets/regions of interests are:

    • identified by the intelligence analyst and photographic interpreter

    • used as ground truth


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Performance Visualisation

  • There are many important dimensions of compression performance

  • Reduction of this complex space to single figures of merit destroys the necessary information

  • Understanding and assimilating this complex space:

    • is a significant problem for the human

    • a multi-dimensional graphical representation is necessary.

  • An interactive performance evaluation visualisation tool facilitates comparison of the performance of different compression approaches:

    • Target cueing in raw/decompressed images;

    • Information preservation;

    • Compression ratio;

    • Computation load;

    • Mean-square-error/Peak Signal-to-noise ratio;

    • Photographic interpreter and intelligence analyst’s assessment.


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Interactive Performance Visualisation

Evaluate and assess:

  • Efficiency and effectiveness of different compression approaches

  • at different compression ratios in different circumstances

  • for different images and different types of images


Master battle planner l.jpg
Master Battle Planner

Situation Awareness, Mission Planning & battle damage assessment


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Evaluation Measures

  • How to measure the effectiveness of compression

  • How to measure the effectiveness of the compressed information in relation to the task:

    • Situation awareness

    • Military activities assessment

    • Monitoring

    • battle damage assessment


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