1 / 13

Image enhancement of Extreme Ultra-Violet Solar Images

Ron Caplan Math 336 Final Presentation December 8 th , 2008. Image enhancement of Extreme Ultra-Violet Solar Images.

vianca
Download Presentation

Image enhancement of Extreme Ultra-Violet Solar Images

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. Ron Caplan Math 336 Final Presentation December 8th, 2008 Image enhancement of Extreme Ultra-Violet Solar Images Images courtesy of SOHO/[instrument] consortium. SOHO is a project of international cooperation between ESA and NASA. where [instrument] stands for the name of the instrument that acquired the data

  2. Overview • Introduction • RAW Data • Pre-processing • Format • Degridding • Stationary Wavelet Transform • Results • My results • Paper’s Results • Conclusion

  3. Introduction • SOHO, the Solar and Heliospheric Observatory, is a project of international cooperation between ESA and NASA to study the Sun, from its deep core to the outer corona, and the solar wind. • One of its many instruments is the Extreme ultraviolet Imaging Telescope (EIT), which provides full disc images of the Sun at four selected colors in the extreme ultraviolet (EUV), mapping the plasma in the low corona and transition region at temperatures between 80,000°C and 500,000°C. • The EIT can image active regions, filaments and prominences, coronal holes, coronal "bright points," polar plumes, loops, and arcades, as well as dynamical events such as flares and mass ejections. • However, the multiscale nature of the observed solar features has not been fully exploited so far. Guillermo Stenborg, AngelosVourlidas, and Russell A. Howard have come up with a wavelet-based processing technique that enhances the EUV images based on their multiscale nature, and reveals features not seen with standard image-processing techniques . They have processed the entire EIT data set with their technique, and has made it available to solar physicists.

  4. Raw Data • uint16 Format(0 -> 65,535) • imagesc(im) • imadjust(im) Issues • Grid patterns • Noise

  5. Pre-Processing • Rescale RAW data extremes:

  6. Pre-Processing • Rescale with imadjust() and convert to uint8 grayscale:

  7. Pre-Processing • De-grid using manual threshold-based notch filter on fft2 of image:

  8. Original • My De-Grid • Official Image

  9. Stationary Wavelet Transform • Kernal (filter) B3-Spline / Biorthogonal 3.3 • Upsample filter at each level (pad with zeros) • Coefficient Matrix 2Nx2N at each level • Set weights for each levels detail coeffs to bring out structure • Also brings out more noise/grid – paper does more processing • MATLAB: swt2.m/iswt2.m

  10. My results • Using 'bior3.3‘, J=5 w=[2 5 4 3 2]: Using officialimage:

  11. My results • Using 'bior3.3‘, J=5 w=[2 5 4 3 2]: Using mydegrid:

  12. ResultsfromPaper • 2-Stage Process • Originalimage • Processedimage Residual Light Model Noise Mask

  13. Conclusion • Process works very well to bring out features not apparent in the images. • Technique is not as simple as it appears…

More Related