UNIVERSITY OF CALIFORNIA,
SANTA CRUZ

 
 
 
 

Hiro (Hiroyuki Takeda. Ph.D.)

Previous (2004 -- 2010)
Multi-Dimensional Signal Processing (MDSP) Lab
Department of Electrical Engineering
Baskin School of Engineering
Email: htakeda AT soe DOT ucsc DOT edu

Current (2010 -- Present)
Postdoctral Research Fellow (website)
Department of Radiology
University of Michigan
Email: htakeda AT umich DOT edu

 
 
 
 

-- Background --

I received the B.S. degree in electronics from Kinki University, Japan, in 2001, and the M.S. and Ph.D. degree in electrical engineering from the University of California, Santa Cruz (UCSC), in 2006 and 2010, respectively. I am currently working as a postdoctoral research fellow in Digital Image Processing Lab, Department of Radiology at the University of Michigan. My research interests are in image processing (motion estimation, interpolation, registration, and super-resolution), inverse problems, and medical imaging (magntic resonance imaging, echo-planar imaging, multi-modal registration).

 
 
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-- Research --

The principal purpose on my research is to produce a superior quality image from an image or several images in low quality by software, instead of implementing expensive and high performance hardware. Nowadays, digital imaging systems are widely used; personal use digital camera, astronomical telescope, medical imaging systems (e.g. CT-Scan, MRI), and so on. Since images given by a CCD array sensor of the systems are often noisy, blurry, and aliased, the necessity of image processing to recover an unknown real scene is getting higher..

 
 
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-- Publications --

Journal Paper:

  1. Takeda, H., S. Farsiu, and P. Milanfar, "Kernel Regression for Image Processing and Reconstruction", IEEE Transactions on Image Processing, Vol. 16, No. 2, pp. 349-366, February 2007.
  2. Takeda, H., S. farsiu, and P. Milanfar, "Deblurring Using Regularized Locally-Adaptive Kernel Regression", IEEE Transactions on Image Processing, Vol. 17, No. 4, pp. 550-563, April 2008.
  3. Protter, M., M. Elad, H. Takeda, and P. Milanfar, "Generalizing the Non-Local-Means to Super-Resolution Reconstruction", IEEE Transactions on Image Processing, Vol. 16, No. 2, pp. 36-51, January 2009.

  4. Takeda, H., P. Milanfar, M. Protter, and M. Elad, "Superresolution without Explicit Subpixel Motion Estimation", IEEE Transactions on Image Processing, Vol. 18, No. 9, September 2009.
  5. H. Takeda and P. Milanfar, "Removing Motion Blur with Space-Time Processing", IEEE Trans. on Image Processing vol. 20, no. 10, October 2011

Conference Paper:

  1. Takeda, H., and P. Milanfar, "Nonlinear Kernel Backprojection for Computed Tomography", To appear in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Dallas, TX, March, 2010.

  2. Takeda, H., and P. Milanfar, "An Adaptive Nonparametric Approach to Restoration and Interpolation for Medical Imaging", Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI): From Nano to Macro, Boston, MA, June, 2009.

  3. Takeda, H., P van Beek, and P. Milanfar, "Spatio-Temporal Video Interpolation and Denoising Using Motion-Assisted Steering Kernel (MASK) Regression", Proceedings of IEEE International Conference on Image Processing (ICIP), San Diego, CA, October 2008.

  4. Takeda, H., HaeJong Seo, and P. Milanfar, "Statistical Approaches to Quality Assessment for Image Restoration", Proceedings of International Conference on Consumer Electronics (ICCE), Las Vegas, NV, January 2008.

  5. Seo, HaeJong.,, P. Chatterjee, H. Takeda, and P. Milanfar, "A Comparison of Some State of the Art Image Denoising Methods", Proceedings of the 41st Asilomar Conference on Signals, Systems, and Computers, 2007

  6. Takeda, H., S. Farsiu, and P. Milanfar, "Higher Order Bilateral Filters and Their Properties", Proceedings of the SPIE Conf. on Computational Imaging, San Jose, January 2007."

  7. Takeda, H., S. Farsiu, and P. Milanfar, "Regularized Kernel Regression for Image Deblurring", Proceedings of the 40th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November 2006.

  8. Takeda, H., S. Farsiu, and P. Milanfar, "Robust Kernel Regression for Restoration and Reconstruction of Images from Sparse Noisy Data", Proceedings of the International Conference on Image Processing (ICIP), Atlanta, GA, October 2006.

  9. Takeda, H., S. Farsiu, J. Christou, P. Milanfar, "Super-Drizzle: Applications of Adaptive Kernel Regression in Astronomical Imaging", Advanced Maui Optical and Space Surveillance (AMOS) Technologies Conference, September 2006.

  10. Takeda, H., S. Farsiu, and P. Milanfar, "Image Denoising by Adaptive Kernel Regression", Proceedings of the 39th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November 2005.

Book Chapter:

  1. H. Takeda and P. Milanfar,"Locally Adaptive Kernel Regression for Space-Time Super-Resolution", To appear as a Chapter in Super-resolution Imaging Edited by P. Milanfar, Available September 27, 2010.

Dissertation:

 
 
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last update on March14th, 2013