Under construction. We will be adding more software packages soon

All of these codes are copyrighted by PI Keigo Hirakawa. The softwares are for research use only. Use of software for commercial purposes without a prior agreement with the authors is strictly prohibited. We do not guarantee the code’s accuracy. Patent applications have been filed for many of these algorithms.  We would appreciate if acknowledgments were made for the use of our codes in your publications.

Adaptive Homogeneity-Directed (AHD) Demosaicking

  • AHD Demosaicking is the default algorithm used in DCRAW.
  • Hirakawa, K., Parks, T.W. (2005): Adaptive homogeneity-directed demosaicing algorithm. In: Image Processing, IEEE Transactions on, 14 (3), pp. 360–369, 2005.
  • [Reference Code][DCRAW]

Macbeth ColorChecker Finder (CCFind)

  • CCFind automatically detects Macbeth ColorChecker inside an image
  • [Reference Code]

Spectrally-Selective Single-Shot High Dynamic Range (S4HDR) Imaging

  • S4HDR takes advantage of the differences in the sensitivities of red, green, and blue pixels to recover high dynamic range images.
  • Hirakawa, K., Simon, P.M. (2011): Single-shot high dynamic range imaging with conventional camera hardware. In: Computer Vision (ICCV), 2011 IEEE International Conference on, pp. 1339 -1346, 2011.
  • [Reference Code][Sample Images]

Blur Processing Using Double Discrete Wavelet Transform (DDWT)

  • DDWT based estimation of motion blur + deblurring (CVPR 2013)
  • DDWT based estimation of defocus blur + deblurring (CVPR 2013)
  • DDWT based camera shake deblurring (work in progress)
  • Yi Zhang, Hirakawa, K. (2013): Blur Processing Using Double Discrete Wavelet Transform. In: Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on, pp. 1091-1098, 2013.
  • [Reference Code]

Color Constancy With Spatio-Spectral Statistics

  • Our color constancy method makes use of  statistical model for the spatial distribution of colors in white balanced images to infer illumination parameters as those being most likely under our model.
  • Chakrabarti, A., Hirakawa, K., Zickler, T. (2012): Color Constancy with Spatio-Spectral Statistics. In: Pattern Analysis and Machine Intelligence, IEEE Transactions on, PP (99), pp. 1, 2012.
  • [Reference Code]

Binning Artifact Removal

  • Although pixel binning significantly improves noise performance of an image sensor, it causes severe aliasing artifacts.  Our binning-aware demosaicking method is designed to eliminate these problems.
  • [Reference Code]

Total Least Squares (TLS) Image Denoising

  • TLS image denoising is designed to work with signal-dependent noise.
  • Hirakawa, K., Parks, T.W. (2006): Image denoising using total least squares. In: Image Processing, IEEE Transactions on, 15 (9), pp. 2730–2742, 2006.
  • [Reference Code]

Coming soon…

  • TLS Joint Demosaicking and Denoising
  • Wavelet Joint Demosaicking and Denoising
  • Spatial-Spectral Color Filter Array Design
  • Skellam (Poisson) Image Denoising
  • Universal Demosaicking
  • Poisson noise parameter estimation