Owing to the stochastic nature of discrete processes such as photon counts in imaging, real-world data measurements
often exhibit heteroscedastic behavior. In particular, time series components and other measurements
may frequently be assumed to be non-iid Poisson random variables, whose rate parameter is proportional to the
underlying signal of interest-witness literature in digital communications, signal processing, astronomy, and
magnetic resonance imaging applications. In this work, we show that certain wavelet and filterbank transform
coefficients corresponding to vector-valued measurements of this type are distributed as sums and differences
of independent Poisson counts, taking the so-called Skellam distribution. While exact estimates rarely admit
analytical forms, we present Skellam mean estimators under both frequentist and Bayes models, as well as
computationally efficient approximations and shrinkage rules, that may be interpreted as Poisson rate estimation
method performed in certain wavelet/filterbank transform domains. This indicates a promising potential
approach for denoising of Poisson counts in the above-mentioned applications.
We present a simple method for estimating the scene illuminant for images obtained by a Digital Still Camera (DSC). The proposed method utilizes basis vectors obtained from known memory color reflectance to identify the memory color objects in the image. Once the memory color pixels are identified, we use the ratios of the red/green and blue/green to determine the most likely illuminant in the image. The critical part of the method is to estimate the smallest set of basis vectors that closely represent the memory color reflectances. Basis vectors obtained from both Principal Component Analysis (PCA) and Independent Component Analysis (ICA) are used. We will show that only two ICA basis vectors are needed to get an acceptable estimate.
We address the periodic clustered tool dot color screen design problem. In traditional clustered dot color screening, the screen for each colorant is rotated to a different angle relative to the others. If the angles are not carefully chosen, visible moire and rosette artifacts may appear. These artifacts primarily result from the interaction of the periodic structures associated with the halftone screens of different colorants. Registration errors can also introduce unwanted artifacts in the screened images. Using lattice theory and a model for the perceived rendered halftone, we present a systematic method for designing moire and rosette free clustered dot color screens for discrete-raster color systems. We also investigate strategies for making the resulting screen robust to registration errors.
Conference Committee Involvement (3)
Video Surveillance and Transportation Imaging Applications 2015
10 February 2015 | San Francisco, California, United States
Video Surveillance and Transportation Imaging Applications 2014
3 February 2014 | San Francisco, California, United States
Video Surveillance and Transportation Imaging Applications
4 February 2013 | Burlingame, California, United States