Daniel A. Lavigne Defence Research and Development Canada Valcartier. Mélanie Breton Aerex Avionics Inc. July 27, 2010

Transcription

1 A new fusion algorithm for shadow penetration using visible and midwave infrared polarimetric images Daniel A. Lavigne Defence Research and Development Canada Valcartier Mélanie Breton Aerex Avionics Inc. Defence Research and Development Canada July 27, 2010 Recherche et développement pour la défense Canada Canada

2 Topics 1. Introduction 2. A new passive polarimetric imaging sensor suite 3. Target detection and shadow penetration using polarized light 4. Experimental measurements 5. Conclusions & Future work

3 1. Introduction Electro-Optical (EO) imaging systems are frequently employed during surveillance operations and search & rescue missions to detect various targets in both the civilian and military communities. The exploitation of the polarization of light can provide additional information about the shape, roughness, and surface characteristics of some targets of interest (man-made objects). It has been demonstrated* that the overall performance of target detection algorithms can be increased by exploiting the polarimetric signatures of targets and discriminate them from cluttered backgrounds. *D.A. Lavigne, M. Breton, G. Fournier, M. Pichette, V. Rivet, Development of performance metrics to characterize the degree of polarization i of man-madeobjects using passive polarimetric images, SPIE Defense and Security Symposium 2009, Signal Processing, Sensor Fusion, and Target Recognition XVIII, Orlando (Florida), April 2009.

4 1. Introduction A new passive polarimetric imaging sensor-suite was designed to collect polarimetric signatures simultaneously using four broadband cameras in the VIS/SWIR/MWIR/LWIR spectral bands: the Visible Infrared Passive Spectral Polarimetric Imager for Contrast Enhancement (VIP SPICE). Hypothesis: It is possible to perform shadow penetration of targets main body parts using the polarimetric signatures of some targets of interest in both the visible and the infrared spectral bands. Ultimate goal: Detection of targets in shadow areas that are currently undetectable by traditional EO imaging systems. Methodology: - Acquire polarimetric signatures of man-made targets using the VIP SPICE sensor suite. - Assess the utility of combining information derived from Stokes vector parameters to perform shadow penetration.

5 2. A new passive polarimetric imaging sensor VIP SPICE: a broadband fully automated remotely controlled four sensor-suite*. 7-filters wheel Front panel Polarizers panel MWIR Visible ( µm) (3 5 µm) LWIR (8 12 µm) SWIR ( µm) Range Finder GPS receiver Visible 30 Pan &Tilt *D.A. Lavigne, M. Breton, G. Fournier, M. Pichette, V. Rivet, A new passive polarimetric imaging system collecting polarization signatures in the visible and infrared bands, SPIE Defense and Security Symposium 2009, Infrared Imaging Systems; Design, Analysis, Modeling, and Testing XX, Orlando (Florida), April 2009.

6 2. A new passive polarimetric imaging sensor 4 Sensors Embedded: Visible ( µm) - CCD camera imager (Lumenera) x 1040 pixels resolution. FOV = 5 o - Linear polarizer (Edmund Optics) - A seven positions filter wheel LWIR(8 12 µm) - Uncooled microbolometer (Nytech) x 480 pixels resolution. FOV = 10 o - Wire-grid ZnSe Reflex polarizer (Analytical Corp.) ) MWIR(3 5 µm) - A focal plane array (platinum silicide) from Mitsubishi x 512 pixels resolution. FOV = 12 o - Wire-grid ZnSe polarizer (Medway Optics) SWIR(1 1.9 µm) - A solid-state InGaAs imager (Sensors Unlimited) x 256 pixels resolution. FOV = 20 o - Aluminum microwires on a glass substrate as a polarizer (Versalight)

7 3. Target detection and shadow penetration The Stokes vector The representation of the radiation backscattered by the targets is computed using the Stokes vector: F 2 2 I Ax + Ay 2 2 A A = Q x y = U 2Ax Ay cosγ V 2Ax Ay sin γ S = S S S I A, A x A y γ Intensity of radiation Amplitudes of the EW in mutually perpendicular directions Phase angle between Ax and Ay S 0 is obtained by passing light waves through linear polarizers oriented at 0 degree. S 1 is obtained by ypassing light waves through linear polarizers oriented at 90 degree. S 2 indicates the excess of radiation in the +45 o direction over that in the +135 o direction relative to the plane of vision. S 3 is the circularly polarized component.

8 3. Target detection and shadow penetration Polarized light Stokes vector parameters computation: Visible band I 0 I 90 I 45 I 135 S 0 = I 0 + I 90 S 1 = I 0 I 90 S 2 = I 45 I 135

9 3. Target detection and shadow penetration Polarized light Computation of Performance Metrics: Degree of Linear Polarization (DoLP): DoLP = S S 0 S 2 2 Polarization angle (φ): ϕ = 1 2 tan 1 S S 2 1 DoLP mapped in pseudo-color

10 3. Target detection and shadow penetration Main Hypothesis: It is possible to perform shadow penetration of targets main body parts using the polarimetric signatures of some targets of interest in both the visible and the infrared spectral bands. The Approach: Targets are detected from their background using the polarimetric and spectral surface characteristics of targets within the scene. A false color rendering of the scene is generated using the information provided by: - the total intensity (S 0 ), - the degree of linear polarization (DoLP), - the polarization angle (φ) of the scene.

11 3. Target detection and shadow penetration The Process: Step 1 Image preprocessing Includes normalization and denoising using state-of-the-art linear filters Step 2 Image coregistration Using multiple automated image co-registration algorithms* Step 3 Calculate Common Component (CC) Local minimum operators are determined in each polarized image CC = S { min{ φ, DoLP} S } 0 DoLP φ = min, 0 *D.A. Lavigne, A fully automated image co-registration system, SPIE Defense and Security Symposium 2006, Signal Processing, Sensor Fusion, and Target Recognition XV, Vol. 6235, Orlando (Florida), April 2006.

12 3. Target detection and shadow penetration The Process: Step 4 Polarized Contributions computation S DoLP * 0 * * β Unique contribution of each polarized image is calculated using modified Common Component information = S0 0 ( S DoLP β ) ( S DoLP β ) ( S DoLP β ) = DoLP 0 = β 0 where β is a measure of polarization* defined by: β 2φ 1 ε ε ε ε ( I ) ε 0 I90 + α + ( I 45 I135 + α ) ε ε ε ε ( I + I + I + I ) = with ε = 0.25 and α = ε *Duggin et al., Contrast enhancement using multiband polarization methods, SPIE Vol.3121, Polarization Analysis, Measurement and Remote Sensing IV, San Diego (CA), 30 July 01 August 1997, pp

13 3. Target detection and shadow penetration The Process: Step 5 Image adjustments Adjusments of the polarized images: remove the computed polarized contributions for each original polarized image ** * * S0 = S0 DoLP β DoLP β ** ** = DoLP S = β * 0 * β * * DoLP S0 Step 6 HSV RGB conversion HSV Images are combined following the conversion HSV to RGB color maps RGB ** ** ** { S, DoLP β } 0,

14 4. Experimental measurements Polarimetric signatures of man-made objects were collected using the VIP SPICE sensor suite during experiments conducted in Summer time in Western Canada. Numerous man-made objects have been used as targets of interest: metallic aluminum plates, SUVs, military vehicles, camouflage nets, etc. Metallic plates Vehicles, tracks, camouflage nets

15 4. Experimental measurements Man-made objects placed within the scene generated shadow areas covering a portion of the objects acquired by the VIP SPICE sensor-suite on the ground and aboard a Genie boom.

16 4. Experimental measurements First experiment Acquisition of an aluminum metallic plate in the Visible band Visible VIP SPICE sensor 25 degrees off-nadir angle 15 meters above ground

17 4. Experimental measurements First experiment Results for the aluminum plate (Visible band) S 0 Computed Polarimetric Images mapped in pseudo-color Metallic plate is segmented from the background 1. Shadowed background 2. Vegetal background 3. Shadowed region of the plate 4. Unshadowed region of the plate

18 4. Experimental measurements Second experiment Acquisition of a SUV in the MWIR spectral band (Ground-based) MWIR

19 4. Experimental measurements Second experiment Results for the SUV (MWIR band) S 0 Computed Polarimetric Images mapped in pseudo-color Tires are segmented in shadow areas Persistent thermal signature detectable below the SUV

20 4. Experimental measurements First experiment Post-processing: edge detection algorithm (e.g. Canny) Visible

21 4. Experimental measurements First experiment Post-processing: edge detection algorithm (e.g. Canny) MWIR

22 5. Conclusions and Future work A new passive polarimetric imaging system was used to acquire polarimetric signatures of man-made objects in the VIS/SWIR/MWIR/LWIR spectral bands. Using the polarized light information gathered from the objects characteristics, the total intensity, the degree of linear polarization, and the phase of polarization have been computed by means of the Stokes vector parameters. Experimental measurements demonstrated the possibility to exploit the polarimetric response of man-made objects for shadow penetration purposes in the visible (VIS) and midwave (MWIR) infrared bands. Future work will involve the development of additional performance metrics to extract information embedded within the polarized signatures of targets of interest. Shadow penetration performance will be assess using other spectral bands (SWIR/LWIR) and supplementary metrics in urban environments.

23 Thank you for your attention Daniel A. Lavigne Defence Research and Development Canada