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Content Based Compression
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Dr. Margaret Varga
Image Processing and Interpretation
Telephone: +44 1684 895712Facsimile: +44 1684 894384Email: [email protected]
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
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
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
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
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
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: