1 / 34

GOES IR Channel to Channel Co-Registration Algorithm and Implementation

GOES IR Channel to Channel Co-Registration Algorithm and Implementation. Zhenping Li@SGT 10/24/2012. Agenda . The channel to channel co-registration algorithm Fast Fourier Transformation Resampling algorithm (FFTR) Image Resampling The implementation OPS concept

natane
Download Presentation

GOES IR Channel to Channel Co-Registration Algorithm and Implementation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. GOES IR Channel to Channel Co-Registration Algorithm and Implementation Zhenping Li@SGT 10/24/2012

  2. Agenda • The channel to channel co-registration algorithm • Fast Fourier Transformation Resampling algorithm (FFTR) • Image Resampling • The implementation • OPS concept • IR Co-registration software package. • SPS implementation • GVAR Change

  3. IR channel to channel co-registration characterization • Uses line-by-line temperature correlation for the channel to channel co-registration approach. • Similar work done by Mike Grotenhuis@STAR • Proposed by ITT • The inputs are from the images in GVAR. • Only the earth pixels are used for the correlation. • The image size must be sufficient large. • Will include full disk, CONUS images, Southern hemisphere, Northern Hemisphere images. • Too much uncertainty for smaller size images (rapid scan), and they will not be included. • The sample size for a given line must be sufficient large, • larger than 1000 pixels after excluding the space pixels for East-West Direction co-registration • Larger than 750 pixels after excluding the space pixels for the North-South Direction. • Using channel 4 as the reference channel, calculating the mis-registration errors of other IR channels relative to Channel 4 in both East-West and North-South direction.

  4. IR channel to channel co-registration characterization • The general steps: • Converting the image into a two dimensional temperature array. • Evaluating the starting and end earth pixel for each line (East-West) or column (North to South) to exclude the space pixels. • Create the input arrays for both channel C and 4 for the earth pixels only. • The linear correlation function can be expressed as the function of mis-registration δ • TC(x) is the channel C temperature at position x, C for 2, 3, and 6. • T4(x+ δ) is the channel 4 temperature at the position x+δ • Perform resampling to evaluate T4(x+ δ). • Obtain the maximum correlation and the corresponding shift for the line or column

  5. Mis-Registration for an Image • The mis-registration for an image is obtained by calculating the weighted average over the mis-registration of each line for East-West Co-registration or each column for North-South Co-registration: • The Ri(δi) is the maximum correlation for the line i in the image. δI is the mis-registration for line i. • Only the line with Ri(δI) >= 0.8 is included in the calculation • Ri(δi) is used as the weight so that the result favors the contributions from the lager correlation

  6. Fourier Transformation and Resampling • Define a global function for the input array in Fourier Expansion form: • N is size of the input array. This approach works better for larger size array. • The resampling array is • The Fast Fourier Transformation (FFT) is used in determine the frequency amplitudes and resampling

  7. Test Case: δ=0 • Blue line is the FFT outputs, and the red dots are the input array. (N=2126) • The maximum difference between data and FFT output is 4x10-4 GVAR counts for GVAR at order of 100 counts

  8. The DFT amplitudes as the functions of frequency • The x-axis corresponds to the ratio k/M, where M is the size of the FFT. • The amplitudes converges quickly as the function of k/M • This is typical behavior for a line in the IR images.

  9. FFT Re-sampling is reversible • In the real operational scenarios, Gδ(x) for a fractional δ is obtained by rounding the FFT output (double value) into the short integer. • One can follow the same procedure to resample Gδ(x) by –δ to obtain the original array, and cast the FFT output into the short integer again. • The conversions of the double variable into the short integer in the re-sampling and reverse re-sampling processes cause the maximum 2 GVAR counts uncertainty. • The test run with δ=0.5 where the uncertainty is largest shows that the max difference of the reversed array and the original array is generally 1 GVAR counts. • The special case: • The maximum difference between data and FFT output is 3x10-3 GVAR counts for GVAR at order of 100 counts • The re-sampling in this case is reversible with no error for integer δ.

  10. The Efficiency • The resampling algorithm using FFT has the efficient of O(Nlog2N). • The algorithm is particularly good for the images with larger sizes. • The time required for the Northern Hemi image (1828x3643) is about 5 seconds on a regular workstations. • Full disk image about 15 seconds. • COUNS Image about 2 seconds. • The efficient meets the latency requirement in the SPS data processing. • Will be further evaluated in the SPS operational environment as a part of the functional test.

  11. The dependence of correlation on the mis-registration using FFTR

  12. Special Case: GOES13 channel 6 to channel 4 co-registration • The channel 6 for GOES13 has one detector, its north-south resolution is half of that for other channels. • The line in channel 6 is off by 0.5 pixel from the lines in other IR channels in North South direction. • The approach: scale channel 6 image so that it has the same resolution as the other IR channels. • Using the FFTR algorithm. is obtained through the image resampling algorithm FFTR from

  13. An example of Channel 6 image: the original image

  14. The scaled Channel 6 image

  15. The Histogram of the scaled and original images • The histogram for the scaled image is divided by 2 since its size is 2 times larger. • The two histograms agree with each other.

  16. The gradient histograms along North-South direction for the original and scaled image • The gradient for the original image is defined as g(x)=Pj-Pj-1 • The gradient for the scaled image is defined as g(x)= Pj+1-Pj-1 • The histogram for the scaled image is divided by 2. • The difference mainly comes from the small pixel value region. • The sharpness of the edges is maintained in the scaled image.

  17. The results: GOES14

  18. Result: GOES15

  19. Results: GOES13

  20. Result Summary • Larger EW mis-registration in 2-4 and 3-4 for GOES14. • 6-4 has been consistently smaller. • Have to perform the resampling for two channels • Either 2,3 or 4,6. • The magnitude of the mis-registration for GOES15 is small. • No resampling is needed. • Lager mis-registration in 2-4 for GOES13 in EW direction. • Larger mis-registration in 6-4 in NS direction with a lot of noises. • All data has a 24 hour periodic behavior. • Overall, mis-registration in 6-4 EW direction is small. • The resampling can be performed in channel 2, 3 or 4,6. • Should look at the landmark to see the mis-registration between IR and visible channels to determine which channels should be resampled.

  21. The co-registration table generation • Least Square Fit the data using the following formula • N=5 in this case, 11 parameters for more than 300 data points • the time t has the hour unit.

  22. The Visible-IR Channel 2 Co-registration and IR EW CORT Table: GOES13 data • The x axis is the number of the half hour increment. • The visible channel is the reference channel • Channel 2 pixel is on the west side of the visible pixel • Channel 2 pixel is on the west side of the channel 4 pixel as well.

  23. The Visible-IR Channel 2 Co-registration and IR EW CORT Table: GOES14 data

  24. The Visible-IR Channel 2 Co-registration and IR CORTTable: GOES15 data

  25. Summary of the resampling approach • Visible-IR2 CORT Table comes from Landmark evaluation from OATS. • The time axis is half hour increment for 24 hour period. • The Visible-IR2 uses Visible channel as reference. • The IR 2-4 co-registration uses channel as the reference. • This leads to the opposite sign in mis-registrations. • The resampling on channels 3, 4, and 6 would be best. • The overall value for GOES14 is small in EW direction for Vis-IR2 • For GOES13, the region where resampling is needed, the value for Vis-IR2 is small in EW direction. • Will not impact on OATS CORT Table generation. • No resampling is needed for GOES15. • The overall value is less than 0.4 pixels in magnitude.

  26. Resample example: Original Image • The image: GOES13 channel 4 at 2012/258/11:15.

  27. Resample Example: the resampled image • The image is shifted by 0.5 pixels

  28. The temperature difference between channel 2 and 4 Before resampling After resampling

  29. Implementation: OPS Concept RPM Archive coreg- retrieval Coreg Table SPS correction GVAR • RPM (Replace Production Monitor) Archive: • Contains 5 days of GVAR data. • Ingested from the realtime GVAR stream. • Used as the input for the IR co-registration evaluation. • coreg-retrieval: • Offline software package to use the GVAR data from RPM archive as the input. • Generates the IR-co-registration table • Only runs when needed, assume that the IR channels co-registraction is relatively stable. • The software package will be installed on CAWS Workstations. • The software is ready to be operational.

  30. OPS Concepts (Continue) • Coreg Table: • IR chan-chan mis-registration table. • An floating number array • Contains 48 elements, and each element corresponding to the mis-registration in every half hour during the 24 hour period. • The output of the coreg-retrieval software package. • The Co-Registration table will be loaded on the SPS database after the new table is generated. • Chan2-chan4 mis-registration value for the specific time will added to GVAR block 0. • SPS perform the resampling on channel 2,3 or 4,6 images to make it align with the images in other IR channels if the mis-registration is larger than certain values (0.5 pixel for example). • This step is optional depends on the user data validation of the channel 4 resampled images. • SPS will have the option to enable or disable the IR channel re-sampling if this is implemented.

  31. OPS Concept (Continue) • If the GVAR images are corrected for mis-registration in IR Channels. • The output of the coreg-retrieval software will be used to monitor the quality of coreg table in the SPS. • The mis-registration retrieved from co-registration corrected images should be very small. • Measuring the difference between the actual mis-registrations and the ones used in the correction. • If the mis-registrations from the co-registration corrected images are larger (>0.3 for example) • The new coreg-table will be created by the combining the coreg-table used in SPS and the output from the coreg-retrieval software. • New table will be loaded into SPS.

  32. Implementation in SPS • Add the IR co-registration tables in SPS database. • Add IR channel to channel mis-registration value to GVAR block 0. • The re-sampling process will performed after the IR calibration. • Adding the control parameter in SPS to enable/disable the resampling function. • Before the straylight correction. • The implementation of the re-sampling process depends on user’s evaluation of the re-sampled image. • Add the re-sampled status word in the GVAR block 0 to indicate if the IR channel images are re-sampled.

  33. Proposed GVAR Block0 Changes GVAR Block 0 with IR channel co-registration. Refer to Table 3-6 in GOES Interface Document 504-02 for complete information

  34. Current Status and Schedule • The Software package for the IR CORT Table generation is ready to be operational. • The resampling code has been migrated to c platform. • SPS implementation is ready to start. • The new version can be released early next year. (Feb-March Timeframe).

More Related