Content Based Compression

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Dr. Margaret Varga

Image Processing and Interpretation

Telephone: +44 1684 895712Facsimile: +44 1684 894384Email: varga@signal.dera.gov.uk

Defence Evaluation & Research AgencyMalvernWorcestershireWR14 3PSUK

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

Current Image Compression Techniques

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

Problems

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– …...

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

Manual Annotation

Quadtree Based Cueing

Phase Congruency

Still Imagery

Video

Motion Surveillance

Cueing Process

Image Fusion

Over-exposed Under-exposed

Fused

Image Fusion

Raw SAR Raw OpticalFused

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

Manual Annotation

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

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

HV Quadtree Parsing

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 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 Congruency

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

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

HV Quadtree Parsing

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 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 Congruency

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

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

MPEG4

RAW Extracted Target Extracted + background

187 frames - small boat in the foreground 800:1

Helicopter Tracking

Performance Evaluation

Performance evaluation is important

Suitable metrication methods must be identified and implemented

Evaluation is a complex and many sided issue

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

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.

Interactive Performance Visualisation

Efficiency and effectiveness of different compression approaches

at different compression ratios in different circumstances

for different images and different types of images

Evaluate and assess:

Master Battle Planner

Situation Awareness, Mission Planning & battle damage assessment

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