Multi spectral imaging

A multispectral image is one that captures image data from two or more ranges of frequencies along the spectrum, such as visible light and infrared energy.

In multispectral images, the same spatial region is captured multiple times using different imaging modalities.

1. 11/9/2014 1 Multi-Spectral Imaging By Alaa Mohammed Khattab

2. Introduction. Electromagnetic Spectrum. Multi-Spectral Imaging. How multi-Spectral Imaging can be used. Multi-Spectral Cameras. Applications. Compression. 11/9/2014 2 Content

3. 11/9/2014 3 Electromagnetic Spectrum

4. Blue : 450-515..520  nm. Used for atmospheric and deep water imaging. Green : 515..520-590..600  nm. Used for imaging of vegetation and deep water structures. Red : 600..630-680..690  nm. Used for imaging of man-made objects. 11/9/2014 4 Visible Light

5. RGB which lie in the visible range can be combined to produce a full color image for viewing on a display. But, RGB are not sufficient to specify the appearance of an object under varying illuminants and viewing conditions. 11/9/2014 5 Visible Light

6. Near infrared : 750-900 nm, is used primarily for imaging of vegetation . Mid-infrared : 1550-1750 nm, is used for imaging vegetation, soil moisture content, and some  forest fires. Far-infrared : 2080-2350 nm, is used for imaging soil, moisture, geological features, silicates, clays, and fires. 11/9/2014 6 Infrared

7. 11/9/2014 7 Green vs. NIR Green Reflectance NIR Reflectance

8. A  multispectral image is one that captures image data from two or more ranges of frequencies along the spectrum, such as visible light and infrared energy. In multispectral images, the same spatial region is captured multiple times using different imaging modalities. 11/9/2014 8 Multi-Spectral Imaging

9. Recording data from the visible spectrum showing an object as it is seen by the eye. Take images in area of spectrum infrared region (invisible). 11/9/2014 9 How can be used

10. Multi-Spectral Imaging 11/9/2014 10

11. Multi- ​spectral sys­tems make it pos­si­ble to look beyond those bound­aries. Quest inno­va­tions is lead­ing in multi-​spectral cam­era tech­nol­ogy. 11/9/2014 11 Multispectral Cameras

12. Higher res­o­lu­tion pic­tures due to larger sensors Able to see in Wave­lengths from 250 – 2200  nm Cam­eras rang­ing from 1 to 5 chan­nels (a reg­u­lar cam­era is 1 channel ) 11/9/2014 12 Multispectral Cameras

13. More chan­nels show sev­eral dif­fer­ent infor­ma­tion layers Cus­tomized soft­ware to ana­lyze every chan­nel sep­a­rately and combined Com­pact and light sys­tems (cam­era, infor­ma­tion stor­age, GPS/​IMU integration ) 11/9/2014 13 Multispectral Cameras

14. Remote Sensing: The sensing platform is usually an aircraft or satellite . The scene being imaged is usually the earth's surface. The sensor and the target are so far apart, so each pixel in the image can correspond to tens or even hundreds of square meters on the ground. 11/9/2014 14 Applications

15. 11/9/2014 15 Applications Athens  as seen by the SPOT 5 satellite in 2002 Spot-5 Satellite French Spot

16. American Thematic mapper sensors feature seven bands of image data (three in visible wavelengths, four in infrared ) 11/9/2014 16 Applications

17. VASARI SYSTEM : VASARI imaging system developed at the National Gallery in London. we are investigating the use of seven filters spanning the visible spectrum. These seven channels can be combined to give accurate measurements. 11/9/2014 17 Applications

18. 11/9/2014 18 Applications

19.   Interpretation of  ancient papyri, such as those found at  Herculaneum, by imaging the fragments in the infrared range (1000 nm ). Used for document inspection and restoration as hidden markings can be become visible in infrared. 11/9/2014 19 Applications

20. 11/9/2014 20 Applications Fingerprint Spoof Detection

21. 11/9/2014 21 Applications Extremely Dry Skin Multispectral Fingerprint Spoof Detection

22. Medical: Multispectral medical images can be formed from different medical imaging modalities such as MRI, CT, and X-ray. These multimodal images are useful for identifying and diagnosing medical disorders . 11/9/2014 22 Applications

23. For example ,The French SPOT and American thematic mapper are older systems, use only a handful of spectral bands. More modern systems, however, can incorporate hundreds of spectral bands into a single image. 11/9/2014 23 Compression

24. It is used to minimize transmission bandwidth from the sensing platform to a ground station and to archive the captured image. Steps: Transformation. Karhunen-Loeve (KL). Frequency transform . Encoding 11/9/2014 24 Compression

25. 11/9/2014 25 Compression

26. The optimal linear transformation for de-correlating the data is the well-known Karhunen-Loeve (KL) transform. Frequency transform such as the discrete cosine (DCT) and wavelet transforms appr oach the optimal KL transform point much more quickly than many other transforms, so they are preferred in actual compression systems. 11/9/2014 26 Transformation

27. Multispectral data can be represented as a 2D image with vector-valued pixels. Each pixel consists of one sample from each image plane All spectral band: sampled at the same resolution. s ampled over the same spatial extent. are perfectly registered, so each pixel component corresponds to the same exact location in the scene. 11/9/2014 27 Transformation

28. Transform-based multispectral coders is categorized into three classes: Spectral-spatial transform. Spatial-spectral transform. Complex spatial-spectral transform. 11/9/2014 28 Transformation

29. All images: Same spatial resolution. Registered. 11/9/2014 29 Spectral-spatial transform :

30. Infrared band may have lower spatial resolution than a visible band. All images: Not the same spatial resolution. Registered. 11/9/2014 30 Spatial-spectral transform :

31. A spatial shift in one image plane relative to another. All images: Not the same spatial resolution. Not registered . 11/9/2014 31 Complex spatial-spectral transform :

32. M ultispectral image compression algorithms fall into two general categories: Lossy . Lossless. 11/9/2014 32 Compression

33. Lossy algorithms typically obtain much higher compression ratios but introduce distortions in the decompressed image. Ex.: RGB color images. Remote sensed data . 11/9/2014 33 Lossy Compression

34. The decoded image is identical to the original. This gives perfect fidelity but limits the achievable compression ratio . Ex .: Medical images. Photographic images. 11/9/2014 34 Lossless Compression

35. Application using multispectral imaging for search: Fingerprint detection. Detection the originality of pages , paints, documents . The discovery of forgery. 11/9/2014 35 Suggested Topics