Slides From ATI Professional Development Short Course             SIGNAL AND IMAGE PROCESSING AND ANALYSIS FOR            ...
www.ATIcourses.comBoost Your Skills                                             349 Berkshire Drive                       ...
Who Am I• Dr. Donald J. Roth is the Nondestructive Evaluation (NDE) Team   Lead at NASA Glenn Research Center as well as a...
Who This Course is Designed For• This course is designed for engineers, scientists,   technicians, implementers, and manag...
The course uses the following model for             much of the time• Discuss Concept• Show Interactive Software Example o...
Digital Signal Processing (DSP)• “Signal” = set of numbers• “Signal” can be 1‐d (generally Amplitude vs. time) or 2‐d   (I...
Smoothing Windows to Reduce Spectral Leakage•   Windowing reduces discontinuities     at boundary of signal thus reducing ...
Smoothing Windows Software Demo                           Turn 2nd                           Signal off                   ...
Limitations of the FFT• No information about how frequencies evolve over time• Not suitable for analyzing impulsive signal...
Advantages of Time‐Frequency Analysis•   Time‐frequency representation shows how frequency components of     a signal evol...
Short‐Time Fourier Transform•   Used to characterize the     Energy Density of a signal as a     function of time and freq...
Short‐Time Fourier Transform Software Demo(Note: Other methods of Joint‐Time Frequency Analysis Provide BetterResolution a...
Practical (Non‐ideal) Filter •   Ideal Filter has                                Characteristics     –   gain = 1 (0 dB) i...
Practical Filter Software Demo                            Start at 10k                            Freq                    ...
Wavelet Transform 1st Level Coefficients Software Demo                                                       Show differen...
Wavelets for Filtering Signals Software Demo• Wavelet Decomposition/Reconstruction Based on Frequency                     ...
Wavelet / Signal Processing of       Terahertz Signals• FS Conditioning (for terahertz signal off of ET foam)             ...
Signal Analysis ‐ Feature Extraction Examples                      SIMULATED VOIDS in FOAM – THz Inspection        Foam 1 ...
Acoustic Emission Signal Analysis DemoControls                                            Results                         ...
Model‐based Curve Fit Software Demos                 19
Image• Image: A spatial   representation of an object;   usually means recorded   image (egs. Of brightness /   intensity)...
Analog vs. Digital Image• Photographic 35 film                • Digital Camera Image                   • Pixelation in dig...
Lookup Table Transformation Example – Linear Contrast                              Expansion•   In the linear histogram of...
Histogram Equalization Example•   Unwanted banding removed, material differences hilited, but noise added                 ...
Lookup Table with Ranging Software Demo                             Change Range,                             Operator,   ...
Image Math Software Demo           25
Image Math – Logical Operators Example         • Grayscale Image AND Grayscale ImageImage1                           Inter...
2d FFT For Images        27
2d FFT Software Filtering Demo                                       Show                                       Camera Man...
Linear Gradient Filter Software Demo                              Change  Kernal#,                              Kernal siz...
Wavelets for Filtering Images • Wavelet Decomposition/Reconstruction Based on Frequency                                   ...
Compacted Soil Phase Analysis        • Automated Analysis        • Clustering Procedure can be used for multiphase        ...
Basic Morphology Operations Software Demo                                  Illustrate                                  Ero...
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Signal & Image Processing And Analysis For Scientists And Engineers Technical Training Short Course


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This three-day course is designed is designed for engineers, scientists, technicians, implementers, and managers who need to understand basic and advanced methods of signal and image processing and analysis techniques for the measurement and imaging sciences. This course will jump start individuals who have little or no experience in the field to implement these methods, as well as provide valuable insight, new methods, and examples for those with some experience in the field.

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Signal & Image Processing And Analysis For Scientists And Engineers Technical Training Short Course

  1. 1. Slides From ATI Professional Development Short Course SIGNAL AND IMAGE PROCESSING AND ANALYSIS FOR SCIENTISTS AND ENGINEERS Instructor: Don J . Roth, Ph.D.ATI Course Schedule: Signal & Image Processing:
  2. 2. www.ATIcourses.comBoost Your Skills 349 Berkshire Drive Riva, Maryland 21140with On-Site Courses Telephone 1-888-501-2100 / (410) 965-8805Tailored to Your Needs Fax (410) 956-5785 Email: ATI@ATIcourses.comThe Applied Technology Institute specializes in training programs for technical professionals. Our courses keep youcurrent in the state-of-the-art technology that is essential to keep your company on the cutting edge in today’s highlycompetitive marketplace. Since 1984, ATI has earned the trust of training departments nationwide, and has presentedon-site training at the major Navy, Air Force and NASA centers, and for a large number of contractors. Our trainingincreases effectiveness and productivity. Learn from the proven best.For a Free On-Site Quote Visit Us At: Our Current Public Course Schedule Go To:
  3. 3. Who Am I• Dr. Donald J. Roth is the Nondestructive Evaluation (NDE) Team  Lead at NASA Glenn Research Center as well as a senior research  engineer with over 27 years of experience in NDE• His primary areas of expertise over his career include research and  development in ultrasonics, thermography, x‐ray, computed  tomography, and terahertz imaging• Served as the deputy discipline expert in NDE for the NASA  Engineering and Safety Center.• Heavily involved in development of NDE‐dedicated software (full  data and control system architectures, and signal and image  processing software systems)• Dr. Roth has published many articles and several book chapters over  this period. His NDE Wave & Image Processor software is available  as a public download at• Dr. Roth consults privately on signal and image processing and  analysis, data visualization, NDE‐related subjects, and LabVIEW  development 2
  4. 4. Who This Course is Designed For• This course is designed for engineers, scientists,  technicians, implementers, and managers who  need to understand current practice and next  generation signal and image processing and  analysis techniques for scientific signal processing  and imaging• Fields where this course would be quite  applicable would be Nondestructive Evaluation,  Diagnostic Medical Imaging, Radar, Sonar,  Security, Earthquake and Acoustic Emission  studies, Digital Filtering, Spectral Analysis, and  many others 3
  5. 5. The course uses the following model for  much of the time• Discuss Concept• Show Interactive Software Example of  Concept – Students get software examples on CD as part of  the course• Show Real World / Case History Example
  6. 6. Digital Signal Processing (DSP)• “Signal” = set of numbers• “Signal” can be 1‐d (generally Amplitude vs. time) or 2‐d  (Image)• Signals can originally be either Digital (Discrete) or Analog  (Continuous) – Phonograph vs. CD Player – Analog signals are converted to digital domain via Analog‐to‐Digital  converter• After acquiring data, DSP answers the question: What next?  5
  7. 7. Smoothing Windows to Reduce Spectral Leakage• Windowing reduces discontinuities  at boundary of signal thus reducing  spectral leakage• Multiply the signal by a finite‐length  x window whose amplitude tapers  smoothly and gradually towards  zero at edges – Changes shape of signal• Or perform convolution of the FFT  spectrum of the original signal with  = the FFT spectrum of the window – Changes signal’s frequency  spectrum • Windowing Reduces Time Domain Frequency  Domain Amplitude of smearing Multiplication Convolution frequencies Convolution Multiplication 6
  8. 8. Smoothing Windows Software Demo Turn 2nd Signal off Turn Filter off Select Windows, Change wave Types & freq For window comparison 7
  9. 9. Limitations of the FFT• No information about how frequencies evolve over time• Not suitable for analyzing impulsive signals that occur  intermittently on top of nominal signal 8
  10. 10. Advantages of Time‐Frequency Analysis• Time‐frequency representation shows how frequency components of  a signal evolve over time • Linear Chirp • Reversed Linear Chirp 9
  11. 11. Short‐Time Fourier Transform• Used to characterize the  Energy Density of a signal as a  function of time and frequency for dynamic signals  – those signals that have  frequency content changing  with time such as dispersive  signals [acoustic emission,  ultrasonic guided waves] 10
  12. 12. Short‐Time Fourier Transform Software Demo(Note: Other methods of Joint‐Time Frequency Analysis Provide BetterResolution as we shall see later)  11
  13. 13. Practical (Non‐ideal) Filter • Ideal Filter has  Characteristics – gain = 1 (0 dB) in passband (PB)  – gain = 0 (‐∞ dB) in the stopband (SB) • Non‐abrupt transition• In practice, there is always finite  • Passband / Stopband ripple transition region between passband  and stopband and/or ripple in both  bands – Gain of filter changes gradually, rather  than abrupty, from 1 to 0• dB = 20log(A0(f)/Ai(f)) describes PB  ripple and SB attenuation – A0(f) = output amplitude at particular  Stopband ripple frequency – Ai(f) = input amplitude at particular  frequency – e.g. SB attenuation = ‐60 dB; (A0(f)/Ai(f))  • Ramifications of Non‐idealness: = 0.001 =10‐3 Filtering does not work perfectly for  Signals and images 12
  14. 14. Practical Filter Software Demo Start at 10k Freq Lowpass filter Move cutoff freq to show attenuation and passing of sine wave Change to Different Freqs and Filters (LP, HP) Then try real world Signals (HOP,  Doppler) with LP & HP filters 13
  15. 15. Wavelet Transform 1st Level Coefficients Software Demo Show different Wavelets at Level 1 See what Analysis  Wavelet and Analysis Scaling Look like Show a 2nd / 3rd data set (blocks, noisy doppler) (UWT representation) Change wavelets Change to L1• Note that Approx coeffs contain lower freqs and detail coeffs contain higher frequency 14
  16. 16. Wavelets for Filtering Signals Software Demo• Wavelet Decomposition/Reconstruction Based on Frequency Show a 2nd / 3rd data set (blocks, noisy doppler, And do reconstructions with  various freq bands selected) (UWT representation) 15
  17. 17. Wavelet / Signal Processing of Terahertz Signals• FS Conditioning (for terahertz signal off of ET foam) Within Gate • Wavelet Denoise • 40x Amplification • DC Subtract 16
  18. 18. Signal Analysis ‐ Feature Extraction Examples SIMULATED VOIDS in FOAM – THz Inspection Foam 1 Foam 1 Peak-centered gate Foam 1 Outlier removal forMetal Contrast enhancement Deeper 17
  19. 19. Acoustic Emission Signal Analysis DemoControls Results Help 18
  20. 20. Model‐based Curve Fit Software Demos 19
  21. 21. Image• Image: A spatial  representation of an object;  usually means recorded  image (egs. Of brightness /  intensity) such as video  image, digital image, or  picture. • For the digital format, an  image can be thought of as  a collection of  measurements at different  spatial positions that form a  2d array. 20
  22. 22. Analog vs. Digital Image• Photographic 35 film • Digital Camera Image • Pixelation in digital image 21
  23. 23. Lookup Table Transformation Example – Linear Contrast  Expansion• In the linear histogram of the  Image Gray Values source image, the gray‐level  intervals [0, 49] and [191, 254]  do not contain significant  information Nearly‐Unused• Using the following LUT  grayscale transformation, any pixel with a  value less than 49 is set to 0,  and any pixel with a value  greater than 191 is set to 255• The interval [50, 190] expands  to [1, 254], increasing the  contrast of the regions with a  Use full range of grayscale concentration of pixels in the  gray‐level range [50, 190] • Widening Gray Range = Contrast Expansion 22
  24. 24. Histogram Equalization Example• Unwanted banding removed, material differences hilited, but noise added 23
  25. 25. Lookup Table with Ranging Software Demo Change Range, Operator, And Image to See effects of Different operations 24
  26. 26. Image Math Software Demo 25
  27. 27. Image Math – Logical Operators Example • Grayscale Image AND Grayscale ImageImage1 Intersection of two images = ANDImage2 • Only way to understand is by doing bitwise ANDing at each pixel 26
  28. 28. 2d FFT For Images 27
  29. 29. 2d FFT Software Filtering Demo Show Camera Man, Lake, Alu Inclusions, Metal Images (these images have energy at low and high Spatial freqs; Also Coin With Jitter live If so desired) Do LP & HP Filter using  ROI mouse draw For metal image, can  On FFT also change  Truncation Frequency = 10%, HP Filter) 28
  30. 30. Linear Gradient Filter Software Demo Change  Kernal#, Kernal size, and Then Images To see effects Of different Gradient filters 29
  31. 31. Wavelets for Filtering Images • Wavelet Decomposition/Reconstruction Based on Frequency • LL2 reconstruction  greatly removes  jagged edges• UltrasonicImage • Note how Of Kennedy wavelet Half Dollar coefficients above  (DWT LL2 emphasize  representation) edges & / or  topography Note: Zoom the Coin Image and Reconstructed  Image To See Detail Removal Better 30
  32. 32. Compacted Soil Phase Analysis • Automated Analysis • Clustering Procedure can be used for multiphase Analysis – in this case, 3 phases • Contrast Expand • Crop • From Automated Clustering Analysis, Porosity (black phase) appears To be ~ 0.20 areal fraction For slice image 181 (cropped region). This analysis also shows white  phases as 0.098 areal fraction. 31
  33. 33. Basic Morphology Operations Software Demo Illustrate Erosion &  Dilation With ‘Salt&Pepper’ And ‘Iron’ Images 32
  34. 34. You have enjoyed ATIs preview of SIGNAL AND IMAGE PROCESSING AND ANALYSIS FOR SCIENTISTS AND ENGINEERS Please post your comments and questions to our blog: Sign-up for ATIs monthly Course Schedule Updates :