Griff L. Bilbro

Demosaicking methods for Bayer color arrays

Digital Still Color Cameras sample the color spectrum using a monolithic array of color filters overlaid on a charge coupled device array such that each pixel samples only one color band. The resulting mosaic of color samples is processed to produce a high resolution color image such that the values of the color bands not sampled at a certain location are estimated from its neighbors. This process is often referred to as demosaicking. This paper introduces and compares a few commonly used demosaicking methods using error metrics like mean squared error in the RGB color space and perceived error in the CIELAB color space.

Optimization of functions with many minima

A numerical method for finding the global minimum of nonconvex functions is presented. The method is based on the principles of simulated annealing, but handles continuously valued variables in a natural way. The method is completely general, and optimizes functions of up to 30 variables. Several examples are presented. A general-purpose program, INTEROPT, is described, which finds the minimum of arbitrary functions, with user-friendly, quasi-natural-language input. >

Optimal thresholding—a new approach

Abstract Finding the optimal threshold(s) for an image with a multimodal histogram is described in well-known literature as a problem in fitting a sum of Gaussians to the histogram. This fitting problem is shown experimentally to be a nonlinear minimization with local minima. A new minimization technique, tree annealing, is presented which finds the global minimum. Experimental results for histograms with two and three modes are presented.

Microwave AlGaN/GaN HFETs

This article presents the operating physics, performance potential, and status of device development of microwave AlGaN/GaN heterostructure field-effect transistors. AlGaN/GaN HFETs show potential for use in improved RF performance microwave amplifier applications. Development progress has been rapid, and prototype devices have demonstrated RF output power density as high as 30 W/mm. Microwave amplifier output power is rapidly approaching 100 W for single-chip operation, and these devices may soon find application for cellular base station transmitter applications. Devices are being developed for use in X-band radars, and RF performance is rapidly improving. The HFET devices experience several physical effects that can limit performance. These effects consist of nonlinearities introduced during the high-current and high-voltage portions of the RF cycle. High-current phenomena involve the operation of the conducting channel above the critical current density for initiation of space-charge effects. The source resistance is modulated in magnitude by the channel current, and high source resistance results. High voltage effects include reverse leakage of the gate electrode and subsequent charge trapping effects on the semiconductor surface, and RF breakdown in the conducting channel. These effects can produce premature saturation effects. Also, under certain conditions, high voltage operation of the device can initiate an IMPATT mode of operation. When this occurs, the channel current increases and RF gain is increased. This phenomenon enhances the RF output power of the device. The physical limiting effects can be controlled with proper design, and the outlook for use of these devices in practical applications is excellent.

Restoration of piecewise-constant images by mean-field annealing

An algorithm is described that removes the noise from images without causing blurring or other distortions of edges. The problem of noise removal is posed as a restoration of an uncorrupted image, given additive noise. The restoration problem is solved by using a new minimization strategy called mean-field annealing (MFA). An a priori statistical model of the image is chosen that drives the minimization toward solutions that are locally homogeneous. The strategy for MFA is derived, and the resulting algorithm is discussed. Applications of the algorithm to both synthetic images and real images are presented.

Performance evaluation of filtered backprojection reconstruction and iterative reconstruction methods for PET images

The filtered backprojection (FBP) algorithm and statistical model based iterative algorithms such as the maximum likelihood (ML) reconstruction or the maximum a posteriori (MAP) reconstruction are the two major classes of tomographic reconstruction methods. The FBP method is widely used in clinical setting while iterative methods have attracted research interests in the past decade. In this paper we studied the performance of the FBP, the ML and the MAP methods using simulated projection data. The experiment showed that the MAP algorithm generated superior image quality in terms of the bias, the variance, and the average mean squared error (MSE) measures.

Focused local learning with wavelet neural networks

A novel objective function is presented that incorporates both local and global errors as well as model parsimony in the construction of wavelet neural networks. Two methods are presented to assist in the minimization of this objective function, especially the local error term. First, during network initialization, a locally adaptive grid is utilized to include candidate wavelet basis functions whose local support addresses the local error of the local feature set. This set can be either user-defined or determined using information derived from the wavelet transform modulus maxima representation. Next, during the network construction, a new selection procedure based on a subspace projection operator is presented to help focus the selection of wavelet basis functions to reduce the local error. Simulation results demonstrate the effectiveness of these methodologies in minimizing local and global error while maintaining model parsimony and incurring a minimal increase on computational complexity.

Extraction of the parameters of equivalent circuits of microwave transistors using tree annealing

The problem of extracting a physically based equivalent circuit model for a heterostructure bipolar transistor (HBT) from S-parameter measurements is solved with a new formulation of simulated annealing. The physical model necessary for an accurate representation of the HBT leads to an extraction problem with many local minima. A satisfactory minimum can be found by conventional gradient-based techniques only with considerable expert guidance. The proposed algorithm finds equivalent circuits as good as those from conventional techniques but without human intervention. It is more efficient than conventional stochastic simulated annealing because it accumulates a probability density of good equivalent circuits which it subsequently uses to refine its statistical search for the best equivalent circuit. >

Mean-field approximation minimizes relative entropy

We derive the mean-field approximation from the information-theoretic principle of minimum relative entropy instead of by minimizing Peierls’s inequality for the Weiss free energy of statistical physics theory. We show that information theory leads to our statistical mechanics procedure. As an example, we consider a problem in binary image restoration. We find that mean-field annealing compares favorably with the stochastic approach.

Sample-sort simulated annealing

A simulated annealing (SA) algorithm called Sample-Sort that is artificially extended across an array of samplers is proposed. The sequence of temperatures for a serial SA algorithm is replaced with an array of samplers operating at static temperatures and the single stochastic sampler is replaced with a set of samplers. The set of samplers uses a biased generator to sample the same distribution of a serial SA algorithm to maintain the same convergence property. Sample-Sort was compared to SA by applying both to a set of global optimization problems and found to be comparable if the number of iterations per sampler was sufficient. If the evaluation phase dominates the computational requirements, Sample-Sort could take advantage of parallel processing.