Peyman Milanfar

Publications

Journal Papers and Book Chapters

  1. A Kheradmand and P. Milanfar, “ A General Framework for Regularized, Similarity-based Image Restoration IEEE Trans. on Image Processing, submitted
  2. H. Talebi and P. Milanfar, “ Nonlocal Image Editing IEEE Trans. on Image Processing, to appear
  3. H. Talebi and P. Milanfar, “ Global Image Denoising IEEE Trans. on Image Processing, vol. 23, no. 2, pp. 755-768, Feb. 2014
  4. X. Zhu, S. Cohen, S. Schiller, and P. Milanfar, “ Estimating Spatially Varying Defocus Blur from A Single Image IEEE Trans. on Image Processing, vol. 22, no. 12, Dec. 2013, pp. 4879-4891
  5. Peyman Milanfar, “ Symmetrizing Smoothing Filters SIAM Journal on Imaging Sciences Vol. 6, No. 1, pp. 263–284
    Also see related talk at SIAM Imaging Science Conference.
  6. H. Talebi, X. Zhu, and Peyman Milanfar, “ How to SAIF-ly Improve Denoising PerformanceIEEE Transactions on Image Processing vol. 22, no. 4, pp. 1470-1485, April 2013
    Also see related project page
  7. Peyman Milanfar, “ A Tour of Modern Image Filtering IEEE Signal Processing Magazine vol. 30, no. 1, January 2013, pp. 106-128 DOI:1053-5888/12/
    Also see related talk at NIPS Workshop 2010.
  8. Chelhwon Kim and Peyman Milanfar, “ Visual Saliency in Noisy Images Journal of Vision ,vol. 13, no. 4 article 5, March 2013. Also see project page .
  9. H.J. Seo and P. Milanfar, Robust Flash Denoising/Deblurring by Iterative Guided Filtering EURASIP Journal on Advances in Signal Processing (Special Issue on Advanced Statistical Tools for Enhanced Quality Digital Imaging with Realistic Capture Models) 2012:3 doi:10.1186/1687-6180-2012-3
    Also see related project page.
  10. F. Sroubek and P. Milanfar, " Robust Multichannel Blind Deconvolution via Fast Alternating Minimization ", IEEE Trans. on Image Processing vol. 21, no. 4, April 2012, pp. 1687 - 1700
  11. X. Zhu and P. Milanfar, " Removing Atmospheric Turbulence via Space-Invariant Deconvolution", IEEE Trans. on Pattern Analysis and Machine Intelligence vol. 35, no. 1, pp. 157-170, Jan. 2013
    Also see related talk and Project page
  12. P. Chatterjee and P. Milanfar, “ Patch-based Near-optimal Image Denoising IEEE Transactions on Image Processing vol. 21, no. 4, April, 2012, pp. 1635-1649
    Also see related project page.
  13. H. Takeda and P. Milanfar, “ Removing Motion Blur with Space-Time Processing ”, IEEE Trans. on Image Processing vol. 20, no. 10, October 2011
    Also see related project page
  14. H.J. Seo and P. Milanfar, “ Face Verification Using the LARK Representation”, To appear in IEEE Transactions on Information Forensics and Security
  15. P. Chatterjee and P. Milanfar, “ Practical Bounds on Image Denoising: From Estimation to Information”, IEEE Trans. on Image Processing, Vol. 20, No. 5, May 2011
  16. H. Takeda and P. Milanfar, “ Locally Adaptive Kernel Regression for Space-Time Super-Resolution”, Book Chapter in Super-resolution Imaging Edited by P. Milanfar, here.
  17. H.J. Seo and P. Milanfar, “ Action Recognition from One Example”, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 33, no. 5 , pp. 867 - 882, May 2011
    Also see related project page. and interview
  18. H.J. Seo and P. Milanfar, “ Static and Space-time Visual Saliency Detection by Self-Resemblance”,  The Journal of Vision 9(12):15, 1-27, http://journalofvision.org/9/12/15/, doi:10.1167/9.12.15
    Also see related project page.
  19. H.J. Seo and P. Milanfar, “ Training-free, Generic Object Detection using Locally Adaptive Regression Kernels”, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 32, no. 9, pp. 1688-1704 , Sept. 2010
    Also see related project page. and interview
  20. X. Zhu and P. Milanfar, “ Automatic Parameter Selection for Denoising Algorithms Using a No-Reference Measure of Image Content”, IEEE Trans. Image Processing vol. 19, no. 12, Dec. 2010
    Also see related project page
  21. M. Offroy, Y. Roggo, P. Milanfar, L. Duponchel, “ Infrared chemical imaging: spatial resolution evaluation and super-resolution concept ”, Analytica Chimica Acta Volume 674, Issue 2, 3 August 2010, Pages 220-226
  22. P. Chatterjee and P. Milanfar, “ Is Denoising Dead?”, IEEE Trans. Image Processing vol. 19, no. 4, pp. 895-911, April 2010
    Also see related project page
  23. P. Chatterjee and P. Milanfar, “ Clustering-based Denoising with Locally Learned Dictionaries”, IEEE Trans. Image Processing vol. 18, no. 7, pp. 1438-1451 , July 2009
    Also see related project page
  24. H. Takeda, and P. Milanfar, M. Protter, M. Elad, “Superresolution Without Explicit Subpixel Motion Estimation ”, IEEE Trans. Image Processing, vol. 18, no. 9, pp. 1958-1975, Sept. 2009
  25. M. Protter, M. Elad, H. Takeda, and P. Milanfar, “Generalizing the Non-Local-Means to Super-resolution Reconstruction ”, IEEE Trans. Image Processing, vol. 18, no. 1, pp. 36-51 , Jan. 2009
  26. H. Takeda, P. van Beek, and P. Milanfar, “ Spatiotemporal Video Upscaling using Motion-Assisted Steering Kernel (MASK) Regression ”, (Book Chapter) to appear in "High-quality visual experience: creation, processing and interactivity of high-resolution and high-dimensional video signals" , Springer-Verlag, 2010
  27. H. Takeda, S. Farsiu, P. Milanfar, “Deblurring Using Regularized Locally-Adaptive Kernel Regression”, IEEE Transactions on Image Processing, vol. 17, no. 4, pp. 550-563, Apr. 2008
    Also see related project page
  28. A. Poonawala, Y. Borodovsky, P. Milanfar “Double Exposure Inverse Lithography”, Microlithography World, 16 (4): 7-9 Nov. 2007.
  29. S. Farsiu, D. Robinson, M. Elad, and P. Milanfar, “Simultaneous Demosaicing and Resolution Enhancement From Under-Sampled Image Sequences”, (Book Chapter) in “Single-Sensor Imaging: Methods and Applications for Digital Cameras,” CRC Press 2008, Rastislav Lukac (Editor), Pages 503-533
  30. L. Duponchel, P. Milanfar, C. Ruckebusch, and J.P Huvenne, “Super-resolution and Raman Chemical Imaging: From Multiple Low Resolution Images to a High Resolution Image”, Analytica Chimica Acta, 607 (2008) pp. 168–175
  31. S. Farsiu, J. Christofferson, B. Eriksson, P. Milanfar, B. Friedlander, A. Shakouri, R. Nowak, “Statistical Detection and Imaging of Objects Hidden in Turbid Media Using Ballistic Photons”, Applied Optics, vol. 46, no. 23, pp. 5805-5822, August 2007
  32. M. Charest, P. Milanfar, “On Iterative Regularization and Its Application”, IEEE Trans. on Circuits and Systems for Video Technology, vol. 18, no. 3, pp. 406-411, March 2008
  33. X. Wang, S. Farsiu, P. Milanfar, and A. Shakouri, “Power Trace: An Efficient Method for Extracting the Power Dissipation Profile in an IC Chip from Its Temperature Map”, IEEE Trans. on Components and Packaging Technologies, vol. 32, no. 2, June 2009, pp:309 - 316
  34. A. Poonawala, P. Milanfar, “A Pixel-Based Regularization Approach to Inverse Lithography”, Microelectronic Engineering, 84 (2007) pp. 2837–2852
  35. A. Poonawala, P. Milanfar, “Double Exposure Mask Synthesis using Inverse Lithography"”, J. Micro/Nanolith. MEMS MOEMS 6(4), 043001, Oct–Dec 2007
  36. D. Robinson, S. Farsiu, P. Milanfar, “Optimal Registration of Aliased Images Using Variable Projection with Applications to Superresolution”, Invited paper, The Computer Journal, 2009 52: 31-42; doi:10.1093/comjnl/bxm007
  37. M. Elad, P. Milanfar, R. Rubinstein, “Analysis versus Synthesis in Signal Priors”, Inverse Problems 23 (2007) pp. 947-968.
  38. A. Poonawala, P. Milanfar, “Mask Design For Optical Microlithography—An Inverse Imaging Problem”, IEEE Trans. on Image Processing, vol. 16, no. 3, pp. 774-788, March 2007.
  39. H. Takeda, S. Farsiu, and P. Milanfar, “Kernel Regression for Image Processing and Reconstruction”, IEEE Trans. on Image Processing, vol. 16, no. 2, pp. 349-366, February 2007.
    Won the IEEE Signal Processing Society Best Paper Award Also see related project page
  40. S. Farsiu, M. Elad, and P. Milanfar, “Video-to-Video Dynamic Superresolution for Grayscale and Color Sequences”, EURASIP Journal of Applied Signal Processing, Special Issue on Superresolution Imaging, Volume 2006, Article ID 61859, Pages 1-15.
    See also: Superresolution Software
  41. M. Shahram, and P. Milanfar, “Statistical and Information-Theoretic Analysis of Resolution in Imaging”, IEEE Transactions on Information Theory, vol. 52, no. 8, pp. 3411-3427, August 2006.
  42. D. Robinson, and P. Milanfar, “Statistical Performance Analysis of Super-resolution”, IEEE Transactions on Image Processing, Vol. 15, no. 6, pp. 1413-1428, June 2006.
  43. R.J. Gardner, M. Kiderlen, and P. Milanfar, “Convergence of algorithms for reconstructing convex bodies and directional measures”, The Annals of Statistics, vol. 34, no. 3, pp. 1331-1374, June 2006.
  44. A. Poonawala, P. Milanfar, R. Gardner, “Shape Estimation from Support and Diameter Functions”, Journal of Mathematical Imaging and Vision 24: pp. 229-244, March 2006.
  45. S. Farsiu, M. Elad, and P. Milanfar, “Multi-Frame Demosaicing and Super-Resolution of Color Images”, IEEE Trans. on Image Processing, vol. 15, no. 1, pp. 141-159, January 2006.
    See also: color version of the paper and Superresolution Software
  46. M. Shahram, and P. Milanfar, “Local Detectors for High-Resolution Spectral Analysis: Algorithms and Performance”, Digital Signal Processing, vol. 15, pp. 305-316, 2005.
  47. D. Robinson, and P. Milanfar, “Bias Minimizing Filter Design for Gradient-Based Image Registration”, Invited Paper, Signal Processing: Image Communication, Volume 20, Issue 6 (Special Issue on Advanced Aspects of Motion Estimation), pp. 554-568, July 2005.
  48. M. Shahram, and P. Milanfar, “On the Resolvability of Sinusoids with Nearby Frequencies in the Presence of Noise”, IEEE Transactions on Signal Processing, vol. 53, no. 7, pp. 2579-2588, July 2005.
  49. A. Cuyt, G.H. Golub, P. Milanfar, B. Verdonk, “Multidimensional Integral Inversion, with Applications in Shape Reconstruction”, SIAM Journal on Scientific Computing, vol. 27, no. 3, pp.1058-1070, 2005.
  50. J. Tsaig, M. Elad, P. Milanfar, and G. Golub, “Variable projection for near-optimal filtering in low bit-rate block coders”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 15, no. 1, pp. 154-160, January 2005.
  51. S. Farsiu, D. Robinson, M. Elad, and P. Milanfar, “Advances and Challenges in Super-Resolution”, Invited Paper, International Journal of Imaging Systems and Technology, Special Issue on High Resolution Image Reconstruction, vol. 14, no. 2, pp. 47-57, 2004.
    See also: Superresolution Software
  52. S. Farsiu, D. Robinson, M. Elad, and P. Milanfar, “Fast and Robust Multi-frame Super-resolution”, IEEE Transactions on Image Processing, vol. 13, no. 10, pp. 1327-1344, October 2004.
    See also: Superresolution Software
  53. G. Boutry, M. Elad, G. Golub, and P. Milanfar, “The Generalized Eigenvalue Problem for Non-Square Pencils Using A Minimal Perturbation Approach”, SIAM Journal On Matrix Analysis and Applications, vol. 27, no. 2, pp. 582-601, 2005.
  54. R. Cosgrove, P. Milanfar, and J. Kositsky, “Trained Detection of Buried Mines in SAR Images via the Deflection Optimal Criterion”, IEEE Transactions on Geoscience and Remote Sensing, vol. 42, no. 11, pp. 2569-2575, November 2004.
  55. D. Robinson, and P. Milanfar, “Fundamental Performance Limits in Image Registration”, IEEE Transactions on Image Processing, vol. 13, no. 9, pp. 1185-1199, September 2004.
  56. M. Elad, P. Milanfar, G.H. Golub, “Shape From Moments—An Estimation Theory Perspective”, IEEE Transactions on Signal Processing, vol. 52, no. 7, pp. 1814-1829, July 2004.
  57. M. Shahram, and P. Milanfar, “Imaging Below the Diffraction Limit: A Statistical Analysis”, IEEE Transactions on Image Processing, vol. 13, no. 5, pp. 677-689, May 2004.
  58. D. Robinson, and P. Milanfar, “Fast Local and Global Projection–based Methods for Affine Motion Estimation”, Invited paper, Journal of Mathematical Imaging and Vision, 18: 35-54, January 2003.
  59. R.J. Gardner, and P. Milanfar, “Reconstruction of Convex Bodies from Brightness Functions”, Discrete and Computational Geometry, 29:279-303, 2003.
  60. N. Nguyen, P. Milanfar, G.H. Golub, “Efficient Generalized Cross-Validation with Applications to Parametric Image Restoration and Resolution Enhancement”, IEEE Transactions on Image Processing, vol. 10, no. 9, pp. 1299-1308, September 2001.
  61. N. Nguyen, P. Milanfar, G.H. Golub, “A Computationally Efficient Image Superresolution Algorithm”, IEEE Transactions on Image Processing, vol. 10, no. 4, pp. 573-583, April 2001.
  62. N. Nguyen, and P. Milanfar, “A Wavelet-Based Interpolation-Restoration Method for Superresolution”, Invited Paper, Circuits, Systems, and Signal Processing, Special issue on advanced signal and image reconstruction, vol. 19, no. 4, pp. 321-338, August 2000.
  63. B. Gustafsson, C. He, P. Milanfar, M. Putinar, “Reconstructing Planar Domains From Their Moments”, Inverse Problems, vol. 16, no. 4, pp. 1053-1070, August 2000.
  64. G. Golub, P. Milanfar, J. Varah, “A Stable Numerical Method for Inverting Shape from Moments”, SIAM Journal on Scientific Computing, vol. 21, no. 4, pp. 1222-1243, December 1999.
  65. P. Milanfar, “A Model of the Effect of Image Motion in the Radon Transform Domain”, IEEE Transactions on Image Processing, vol. 8, no. 9, pp. 1276-1281, September 1999.
    See also the longer version Technical Report
  66. P. Milanfar, “Two Dimensional Matched Filtering for Motion Estimation”, IEEE Transactions on Image Processing, vol. 8, no. 3, pp. 438-443, March 1999.
  67. P. Milanfar, “A Persian Folk Method of Figuring Interest”, Mathematics Magazine, vol. 69, no. 5, December 1996.
  68. P. Milanfar, “Projection-based, Frequency-Domain Estimation of Superimposed Translational Motions”, Journal of the Optical Society of America: A, Optics and Image Science, vol. 13, no. 11, pp. 2151-2162, November 1996.
  69. P. Milanfar, and J.H. Lang, “Monitoring the Thermal Condition of Permanent-Magnet Synchronous Motors”, IEEE Transactions on Aerospace and Electronic Systems, vol. 32, no. 4, pp. 1421-1429, October 1996.
  70. P. Milanfar, “On the Hough Transform of a Polygon”, Pattern Recognition Letters, vol. 17, pp. 209-210, February 1996.
  71. P. Milanfar, W.C. Karl, A.S. Willsky, “A Moment-based Variational Approach to Tomographic Reconstruction”, IEEE Transactions on Image Processing, vol. 5, no. 3, pp. 459-470, March 1996.
  72. P. Milanfar, G.C. Verghese, W.C. Karl, A.S. Willsky, “Reconstructing Polygons from Moments with Connections to Array Processing”, IEEE Transactions on Signal Processing, vol. 43, no. 2, pp. 432-443, February 1995.
  73. P. Milanfar, W.C. Karl, A.S. Willsky, “Reconstructing Binary Polygonal Objects from Projections: A Statistical View”, CVGIP: Graphical Models and Image Processing, vol. 56, no.5, pp. 371-391, September 1994.

Conference Publications and Presentations

  1. H. Talebi and P. Milanfar, “ Global Denoising is Asymptotically Optimal International Conference on Image Processing (ICIP) , Oct. 2014, Paris
  2. S. Biswas Kumar and P. Milanfar, “ Laplacial Object: One-shot Object Detection by Locality Preserving Projection International Conference on Image Processing (ICIP) , Oct. 2014, Paris
  3. H. Talebi and P. Milanfar, “ Global Image Editing Using the Spectrum of Affinity Matrices GlobalSIP Symposium on Mobile Imaging , Dec. 2013, Austin, TX
  4. A. Kheradmand and P. Milanfar, “ A General Framework for Kernel Similarity-based Image Denoising GlobalSIP Symposium on Graph Signal Processing , Dec. 2013, Austin, TX
  5. X. Zhu, and P. Milanfar, “ Qpro: An improved no-reference image content metric using locally adapted SVD Proceedings of Seventh International Workshop on Video Processing and Quality Metrics for Consumer Electronics, January 2013, Scottsdale, Arizona
  6. J. Kotera, F. Sroubek, and P. Milanfar, “ Blind deconvolution using alternating maximum a posteriori estimation with heavy-tailed priors 15th International Conference on Computer Analysis of Images and Patterns , Aug. 2013, York, UK
  7. X. Zhu, F. Sroubek, and P. Milanfar, “ Deconvolving PSFs for A Better Motion Deblurring using Multiple Images European Conference on Computer Vision (ECCV), Oct. 2012, Florence, Italy
    Also see related Software package
  8. H. Talebi and P. Milanfar, “ Improving Denoising Filters by Optimal Diffusion International Conference on Image Processing (ICIP), Sept. 2012, Orlando, FL
  9. E. Matlin and P. Milanfar, “ Removal of Haze and Noise from a Single Image SPIE Conference on Computational Imaging (8269) , January 2012, Burlingame, CA
  10. C. Kim and P. Milanfar, “ Finding Saliency in Noisy Images SPIE Conference on Computational Imaging (8269) , January 2012, Burlingame, CA
  11. H. Talebi and P. Milanfar, “ Patch-wise Ideal Stopping Time for Anisotropic Diffusion SPIE Conference on Visual Information Processing and Communication (8305) , January 2012, Burlingame, CA
  12. H. Seo and P. Milanfar, " Iteratively Merging Information from a Pair of Flash/no-Flash Images using Nonlinear Diffusion ", International Conference on Computer Vision (ICCV), Workshop on Information Theory in Computer Vision, Barcelona, Nov. 2011
    Also see related Project page
  13. X. Zhu and P. Milanfar, " Stabilizing and Deblurring Atmospheric Turbulence ", International Conference on Computational Photography (ICCP), April 8-10, Carnegie Mellon University, Pittsburgh, 2011
    Also see related talk and Project page
  14. P. Chatterjee and P. Milanfar, “ Patch-based Locally Optimal Denoising IEEE International Conference on Image Processing , 2011, Brussels
    Also see related project page.
  15. F. Sroubek, J. Kamenicky and P. Milanfar, “ Superfast Superresolution IEEE International Conference on Image Processing , 2011, Brussels
  16. X. Zhu and P. Milanfar, " A No-Reference Image Content Metric and Its Application to Denoising ", IEEE International Conference on Image Processing (ICIP), Hong Kong, September 2010
  17. X. Zhu and P. Milanfar, " Restoration for Weakly Blurred and Strongly Noisy Images ", IEEE Workshop on Applications of Computer Vision (WACV), Kona, Hawaii, January 2011
    Also see related software pacakge
  18. P. Chatterjee and P. Milanfar, " Learning Denoising Bounds for Noisy Images ", IEEE International Conference on Image Processing (ICIP), Hong Kong, September 2010
  19. X. Zhu and P. Milanfar, " Image Reconstruction from Videos Distorted by Atmospheric Turbulence ", SPIE Electronic Imaging, Conference 7543 on Visual Information Processing and Communication, San Jose, CA, 2010.
  20. P. Chatterjee, and P. Milanfar, “ Fundamental Limits of Image Denoising: Are we there yet? ”, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Dallas, March, 2010
  21. H. Takeda , and P. Milanfar, “ Nonlinear Kernel Backprojection for Computed Tomography ”, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Dallas, March, 2010
  22. H.J. Seo, and P. Milanfar, “ Visual Saliency for Automatic Target Detection, Boundary Detection, and Image Quality Assessment ”, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Dallas, March, 2010
  23. H.J. Seo, and P. Milanfar, “ Nonparametric Detection and Recognition of Visual Objects from a Single Example ”, Workshop on Defense Applications of Signal Processing (DASP), Kaua'i, HI, September, 2009
  24. P. Chatterjee, and P. Milanfar, “ Bias Modeling for Image Denoising ”, Asilomar Conference on Signals and Systems, Pacific Grove, CA, November, 2009
  25. H. Takeda, H.J. Seo, and P. Milanfar, “ Adaptive Regression Kernels for Image/Video Restoration and Recognition ”, in Frontiers in Optics 2009/Laser Science XXV/Computational Optical Sensing and Imaging/Signal Recovery and Synthesis, San Jose, CA, October, 2009
  26. H.J. Seo, and P. Milanfar, “ Detection of Human Actions From A Single Example ”, IEEE International Conference on Computer Vision (ICCV), Kyoto, September, 2009
  27. H.J. Seo, and P. Milanfar, “ A Non-parametric Approach to Automatric Change Detection in MRI Images of The Brain ”, IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Boston, June, 2009
  28. X. Zhu, and P. Milanfar, “ A No-Reference Sharpness Metric Sensitive to Blur and Noise ”, 1st International Workshop on Quality of Multimedia Experience (QoMEX), San Diego, July 2009
  29. H. Takeda, and P. Milanfar, “ An Adaptive Nonparamtric Approach to Restoration and Interpolation for Medical Imaging ”, IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Boston, June, 2009
  30. H.J. Seo, and P. Milanfar, “ Nonparametric Bottom-Up Saliency Detection by Self-Resemblance ”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 1st International Workshop on Visual Scene Understanding (ViSU’09), Miami, June, 2009
  31. P. Chatterjee, and P. Milanfar, “ Image Denoising using Locally Learned Dictionaries ”, Proceedings of SPIE Electronic Imaging, Conference 7246 on Computational Imaging, San Jose, CA, January 2009.
  32. H. Seo, and P. Milanfar, “ Using Local Regression Kernels for Statistical Object Detection ”, Proceedings of IEEE International Conference on Image Processing (ICIP), San Diego, CA, October 2008.
  33. H. Takeda, 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.
  34. H. Seo, and P. Milanfar, “Video Denoising Using Higher Order Optimal Space-Time Adaptation ”, Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 1249-1252, Las Vegas, NV, March 2008.
  35. P. Chatterjee, and P. Milanfar, “A Generalization of Non-Local Means via Kernel Regression ”, Proc. of the SPIE Conf. on Computational Imaging, San Jose, January 2008.
  36. H. Takeda, H. Seo, P. Milanfar, “Statistical Approaches to Quality Assessment for Image Restoration”, Invited paper in Proceedings of the International Conference on Consumer Electronics, Las Vegas, NV, January 2008.
  37. H. Seo, P. Chatterjee, H. Takeda, P. Milanfar, “A Comparison of Some State of the Art Image Denoising Methods”, Proceedings of the 41st Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November 2007.
  38. D. Robinson, S. Farsiu, J. Lo, P. Milanfar, C.A. Toth, “Efficient Registration of Aliased X-Ray Images”, Proceedings of the 41st Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November 2007.
  39. S. Farsiu, and P. Milanfar, “Multi-Scale Statistical Detection and Ballistic Imaging Through Turbid Media”, To appear in Proc. of the IEEE International Conference on Image Processing (ICIP), San Antonio, TX, September 2007.
  40. X. Wang, A. Shakouri, S. Farsiu and P. Milanfar, “Extraction of Power Dissipation Profile in an IC Chip From Temperature Map”, Proc. of 23rd Semiconductor Thermal Measurement, Modeling, and Management (SemiTherm) Symposium, San Jose, CA, March 2007.
  41. A. Poonawala, Y. Borodovsky, and P. Milanfar, “ILT for Double Exposure Lithography with Conventional and Novel Materials”, Proceedings of the SPIE Advanced Lithography Symposium, February 2007.
  42. H. Takeda, S. Farsiu, and P. Milanfar, “Higher Order Bilateral Filters and Their Properties”, Proc. of the SPIE Conf. on Computational Imaging, San Jose, January 2007.
  43. H. Takeda, 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.
  44. H. Takeda, S. Farsiu, P. Milanfar, “Robust Kernel Regression for Restoration and Reconstruction of Images from Sparse, Noisy Data”, to appear in Proc. of the International Conference on Image Processing, Atlanta, GA, October 2006.
    See also: Kernel Regression-Based Image Processing ToolBox for MATLAB
  45. H. Takeda, 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.
  46. M. Elad, P. Milanfar, R. Rubinstein, “Analysis versus synthesis in signal priors”, EUSIPCO, Florence, Italy, September 4-8, 2006.
  47. M. Charest, M. Elad, P. Milanfar, “A General Iterative Regularization Framework For Image Denoising”, Proc. of the 40th Conference on Information Sciences and Systems, Princeton, NJ, March 2006.
  48. A. Poonawala, and P. Milanfar, “OPC and PSM design using inverse lithography: A non-linear optimization approach”, Proc. of the SPIE Conference on Optical Microlithography XIX, San Jose, February 2006.
  49. D. Odom, and P. Milanfar, “Modeling Multiscale Differential Pixel Statistics”, Proc. of the SPIE Conf. on Computational Imaging, San Jose, January 2006.
  50. S. Farsiu, M. Elad, and P. Milanfar, “A Practical Approach to Super-Resolution”, Invited paper, Proc. of the SPIE Conf. on Visual Communications and Image Processing, San Jose, January 2006.
  51. H. Takeda, 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.
    See also: Kernel Regression-Based Image Processing ToolBox for MATLAB and Kernel Regression for Image Processing and Reconstruction—example results
  52. S. Farsiu, M. Elad, P. Milanfar, “Constrained, Globally Optimal, Multi-frame Motion Estimation”, Proc. of the 2005 IEEE Workshop on Statistical Signal Processing, Bordeaux, France, July 2005.
  53. P. Milanfar, “Resolution and Its Enhancement in Imaging” (Extended abstract), Invited Talk, Optical Society of America Topical Meeting on Signal Recovery and Synthesis, Charlotte, North Carolina, June 2005.
  54. A. Poonawala, and P. Milanfar, “Prewarping Techniques in Imaging: Applications to Nanotechnology and Biotechnology”, Proceedings of SPIE Vol. 5674, SPIE Electronic Imaging, Conference on Computational Imaging III, San Jose, CA, January 2005.
  55. L. Zimet, M. Shahram, P. Milanfar, “An Adaptive Framework for Image and Video Sensing”, Proceedings of SPIE Vol. 5678, SPIE Electronic Imaging, Conference on Digital Photography, San Jose, CA, January 2005.
  56. M. Shahram, and P. Milanfar, “Improved Spectral Analysis of Nearby Tones Using Local Detectors” (Won best student paper award), Proceedings of the 2005 International Conference on Acoustic, Speech, and Signal Processing, Philadelphia, Pennsylvania, March 2005.
  57. A. Cuyt, G. Golub, P. Milanfar, B. Verdonk, “Inverting a Multidimensional Shape From Moments”, Proceedings of the International Conference on Numerical Analysis and Applied Mathematics / Simos T.E. [edit.], Weinheim, Wiley, p. 436-439, 2004.
  58. D. Robinson, and P. Milanfar, “Statistical Performance Analysis of Superresolution Image Reconstruction”, Proceedings of the 38th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November 2004.
  59. S. Farsiu, D. Robinson, M. Elad, and P Milanfar, “Dynamic Demosaicing and Color Super-Resolution of Video Sequences”, Proceedings of SPIE Conference on Image Reconstruction from Incomplete Data III - Volume 5562, October 2004.
  60. S. Farsiu, M. Elad, P. Milanfar, “Multi-Frame Demosaicing and Super-Resolution from Under-Sampled Color Images”, Proceedings of the SPIE Conference on Computational Imaging, Jan. 18-22, 2004, San Jose, CA.
    See also: Superresolution Software
  61. Segall, A., M. Elad, P. Milanfar, R. Webb and C. Fogg, “Improved High-Definition Video by Encoding at an Intermediate Resolution”, Proceedings of the SPIE Conference on Visual Communications and Image Processing, Jan. 18-22, 2004, San Jose, CA.
  62. D. Robinson, P. Milanfar, “Bias Minimizing Filters for Gradient-Based Motion Estimation”, Proceedings of the 37th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA. November 2003. (Won 2nd place in the student paper competition).
  63. A. Poonawala, P. Milanfar, R. Gardner, “On the Uncertainty Analysis of Shape Reconstruction from Areas of Silhouettes”, to appear in Proceedings of Fifth International Conference on Advances In Pattern Recognition, Calcutta, India, December 2003.
  64. M. Shahram, and P. Milanfar, “A Statistical Analysis of Achievable Resolution in Incoherent Imaging”, Proceedings of the SPIE Annual Meeting, San Diego, CA, August 2003.
  65. S. Farsiu, D. Robinson, M. Elad, P. Milanfar, “Robust Shift-and-Add Approach to Super-resolution”, Proceedings of the SPIE Annual Meeting, San Diego, CA, August 2003.
    See also: Superresolution Software
  66. D. Robinson, and P. Milanfar, “Fundamental Performance Limits in Image Registration”, Proceedings of the 2003 IEEE International Conference on Image Processing, Barcelona.
  67. S. Farsiu, D. Robinson, M. Elad, P. Milanfar, “Fast Robust Superresolution”, Proceedings of the 2003 IEEE International Conference on Image Processing, Barcelona.
    See also: Superresolution Software
  68. J. Tsaig, M. Elad, G.H. Golub, P. Milanfar, “Optimal Framework for Low Bit-Rate Block Coders”, Proceedings of the 2003 IEEE International Conference on Image Processing, Barcelona.
  69. X. Feng, and P. Milanfar, “Multiscale Principal Components Analysis for Image Local Orientation Estimation”, Proceedings of the 36th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, November 2002.
    See also: Orientation Estimation Software
  70. A. Poonawala, P. Milanfar, R. Gardner, “A Statistical Analysis of Shape Reconstruction From Areas of Shadows”, Invited paper, Proceedings of the 36th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, November 2002.
  71. M. Elad, P. Milanfar, G.H. Golub, “Shape From Moments as an Inverse Problem”, Proceedings of the 36th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, November 2002.
  72. J. Kositsky, R. Cosgrove, C. Amazeen, P. Milanfar, “Results from a Forward-Looking GPR Mine Detection System”, Proceedings of SPIE Conference on Detection and Remediation Technologies for Mines and Minelike Targets VII, Vol. 4742.
  73. P. Milanfar, and A. Shakouri, “A Statistical Analysis of Diffraction-limited Imaging”, Proceedings of the International Conference on Image Processing, pp. 864-867, September 2002.
  74. M. Elad, P. Milanfar, G.H. Golub, “Shape From Moments—An Estimation Theory Perspective”, Invited Talk, The SIAM 50th Anniversary Meeting, July 2002, Philadelphia, PA.
  75. D. Robinson, and P. Milanfar, “Efficiency and Accuracy Tradeoffs in using Projections for Motion Estimation”, Proceedings of the 35th Asilomar Conference on Signals, Systems, and Computers, November 2001. (Won 3rd place in the best student paper competition)
  76. P. Milanfar, and R. J. Gardner, “Shape Reconstruction from Brightness Functions”, Invited paper, Proceedings of SPIE Vol. 4474, SPIE Conference on Advanced Signal Processing Algorithms, Architectures, and Implementations X, August 2001, San Diego, CA.
  77. N. Nguyen, and P. Milanfar, “An Efficient Wavelet-Based Algorithm for Image Superresolution”, Proceedings of the IEEE International Conference on Image Processing, Vancouver, B.C., Canada, September 10-13, 2000.
  78. P. Milanfar, M. Putinar, J. Varah, B. Gustafsson, and G. Golub, “Shape Reconstruction From Moments: Theory, Algorithms, and Applications”, Invited paper, Proceedings of SPIE Vol. 4116, SPIE Conference on Advanced Signal Processing Algorithms, Architectures, and Implementations X, August 2000, San Diego, CA.
  79. N. Nguyen, P. Milanfar, and G. Golub, “Blind Superresolution with Generalized Cross-Validation using Gauss-type Quadrature Rules”, Thirty-third Asilomar Conference on Signals, Systems, and Computers, October 24-27, 1999.
  80. J. Kositsky, and P. Milanfar, “A Forward-Looking High-Resolution GPR System”, SPIE Vol. 3710, Proceedings of Aerosense '99, Part of SPIE Conference on Detection and Remediation Technologies for Mines and Minelike Targets IV, Orlando, Florida, April 1999.
  81. N. Nguyen, P. Milanfar, and G. Golub, “Preconditioners for Regularized Image Superresolution”, Proceedings of IEEE ICASSP, March 15-19, 1999, Phoenix, Arizona.
  82. P. Milanfar, “Motion From Projections: A Forward Model”, Proceedings of the International Conference on Image Processing, October 1998, Chicago, IL.
  83. N. Nguyen, P. Milanfar, and G. Golub, “Preconditioners for Super-resolution Reconstruction”, Fifth Copper Mountain Conference on Iterative Methods, March 30-April 3, 1998, Copper Mountain, Colorado.
  84. P. Milanfar, “Fast Geometric Algorithms for Tomographic Nondestructive Evaluation of Civil Structures”, Proceedings of the International Symposium on Nondestructive Testing in Civil Engineering, September 26-28, 1995, Berlin, Germany.
  85. P. Milanfar, R.R. Tenney, R.B. Washburn, A.S. Willsky, “Modeling and Estimation for a Class of Multiresolution Random Fields”, Proceedings of the IEEE International Conference on Image Processing, Austin, TX, November 1994.
  86. P. Milanfar, W.C. Karl, A.S. Willsky, and G.C. Verghese, “Moment-based Geometric Image Reconstruction”, Proceedings of the IEEE International Conference on Image Processing, Austin, TX, November 1994.
  87. T. Kurien, P. Milanfar, D. Logan, “Propagation Mode Estimation: A Requirement for OTH Data Fusion”, Proceedings of the IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, Las Vegas, NV, October 1994.
  88. P. Milanfar, W.C. Karl, A.S. Willsky, G.C. Verghese, “Polygon Reconstruction from Moments Using Array Processing”, Proceedings of the Sixth IEEE Digital Signal Processing Workshop, Yosemite National Park, CA, October 1994.
  89. P. Milanfar, M. Bhatia, L.A. Belcastro, S. Jaggi, W.C. Karl, A.S. Willsky, “Geometric and Multiresolution Statistical Methods for Reconstruction from Projections”, Proceedings of the IEEE Eighth Workshop on Multidimensional Signal Processing, Cannes, France, September 1993.
  90. P. Milanfar, W.C. Karl, and A.S. Willsky, “Statistical Approaches to the Tomographic Reconstruction of Finitely Parameterized Geometric Objects”, Proceedings of the SPIE 1992 Intl. Symposium: Neural and Stochastic Methods in Image and Signal Processing, San Diego, CA, July 1992.
  91. P. Milanfar, and J.H. Lang, “Monitoring the Thermal Condition of Permanent-Magnet Synchronous Motors”, Proceedings of the IEEE Industrial Applications Society Annual Meeting, October 1991.

Dissertations

  1. Xiang Zhu, Ph.D. Thesis, “ Measuring Spatially Varying Blur and Its Application in Digital Image Restoration ”, Electrical Engineering, UC Santa Cruz, June 2013.
  2. Erik Matlin, M.S. Thesis, “Single Image Haze and Noise Removal ”, Electrical Engineering, UC Santa Cruz, June 2011.
  3. Priyam Chatterjee, Ph.D. Thesis, “Patch-based Image Denoising and Its Performance Limits ”, Electrical Engineering, UC Santa Cruz, June 2011.
  4. Haejong Seo, Ph.D. Thesis, “ Robust Visual Recognition with Locally Adaptive Regression Kernels”, Electrical Engineering, UC Santa Cruz, June 2011.
  5. Hiroyuki Takeda, Ph.D. Thesis, “ Locally Adaptive Kernel Regression Methods for Multi-dimensional Signal Processing”, Electrical Engineering, UC Santa Cruz, September 2010.
  6. Amyn Poonawala, Ph.D. Thesis, “Mask Design for Single and Double Exposure Optical Microlithography: An Inverse Imaging Approach”, Computer Engineering, UC Santa Cruz, September 2007.
  7. David Odom, M.S. Thesis, “Differential Pixel Statistic Based Priors for Image Restoration”, Electrical Engineering, UC Santa Cruz, June 2006.
  8. Michael Charest, M.S. Thesis, “A General Framework for Iterative Regularization in Image Processing”, Electrical Engineering, UC Santa Cruz, June 2006.
  9. Hiroyuki Takeda, M.S. Thesis, “Kernel Regression for Image Processing and Reconstruction”, Electrical Engineering, UC Santa Cruz, March 2006.
  10. Sina Farsiu, Ph.D. Thesis, “A Fast and Robust Framework for Image Fusion and Enhancement”, Electrical Engineeting, UC Santa Cruz, December 2005.
  11. Morteza Shahram, Ph.D. Thesis, “Statistical and Information-Theoretic Analysis of Resolution in Imaging and Array Processing”, Electrical Engineering, UC Santa Cruz, June 2005.
  12. Lior Zimet, M.S. Thesis, “An Adaptive Framework for Image and Video Sensing”, Electrical Engineering, UC Santa Cruz, March 2005.
  13. Dirk Robinson, Ph.D. Thesis, “Estimation Theoretic Analysis of Motion in Image Sequences”, Electrical Engineering, UC Santa Cruz, December 2004.
  14. Amyn Poonawala, M.S. Thesis, “Reconstructing Shapes from Support and Brightness Functions”, Computer Engineering, UC Santa Cruz, March 2004.
  15. XiaoGuang Feng, M.S. Thesis, “Analysis and Approaches to Image Local Orientation Estimation”, Computer Engineering, UC Santa Cruz, March 2002.
  16. Nhat Nguyen, Ph.D. Thesis, “Numerical Algorithms for Image Super-Resolution”, Scientific Computing and Computational Mathematics Program, Stanford University, July 2000.
  17. Peyman Milanfar, Ph.D. Thesis, “Geometric Estimation and Reconstruction From Tomographic Data”, Electrical Engineering and Computer Science, M.I.T., June 1993.
  18. Peyman Milanfar, S.M. Thesis, “Failure Monitoring in Small Permanent-Magnet Synchronous Motors”, Electrical Engineering and Computer Science, M.I.T., October 1990.