Image destriping

From HandWiki

Image destriping is the process of removing stripes or streaks from images and videos. These artifacts plague a range of fields in scientific imaging including atomic force microscopy,[1] light sheet fluorescence microscopy,[2] and planetary satellite imaging.[3] Common to all of these systems, stripe artifacts appear as horizontal or vertical banding that extend most or all of the image. Removal of stripe artifacts is necessary for accurate scientific interpretation, machine vision applications, or image aesthetic.

The most common image processing techniques to reduce stripe artifacts is with Fourier filtering [4]. Unfortunately, filtering methods risk altering or suppressing useful image data. Methods developed for multiple-sensor imaging systems in planetary satellites use statistical-based methods to match signal distribution across multiple sensors[5]. More recently, a new class of approaches leverage compressed sensing, to regularize an optimization problem, and recover stripe free images[6] [7]. In many cases, these destriped images have little to no artifacts, even at low signal to noise rations[7].


References

  1. Chen, S. W.; Pellequer, J. L. (2011). "DeStripe: frequency-based algorithm for removing stripe noises from AFM images.". BMC Structural Biology 11: 1–10. 
  2. Liang, X.; Zang, Y.; Dong, D.; Zhang, L.; Fang, M.; Arranz, A.; Ripoll, J.; Hui, H. et al. (2016). "Stripe artifact elimination based on nonsubsampled contourlet transform for light sheet fluorescence microscopy.". Journal of Biomedical Optics 21: 106005–106010. 
  3. Rakwatin, P.; Takeuchi, W.; Yasuoka, Y. (2007). "Stripe Noise Reduction in MODIS Data by Combining Histogram Matching With Facet Filter.". IEEE Transactions on Geoscience and Remote Sensing 45: 1844–1856. 
  4. Chen, J.; Shao, Y; Guo, H.; Wang, W.; Zhu, B. (2003). "Destriping CMODIS data by power filtering.". IEEE Trans Geosci Remote Sens 41: 2119-2124. 
  5. Gadallah, F.L.; Csillag, F; Smith, E.J.M. (2010). "Destriping multisensor imagery with moment matching.". Int J Remote Sens 21: 2505–2511. 
  6. Fitschen, J.H.; Ma, J; Schuff, S. (2017). "Removal of curtaining effects by a variational model with directional forward differences.". Comput Vis Image Underst 155: 24-32. 
  7. 7.0 7.1 Schwartz, J.; Jiang, Y; Bassim, N.; Hovden, R. (2019). "Removing Stripes, Scratches, and Curtaining with Nonrecoverable Compressed Sensing.". Microscopy and Microanalysis.