Michael J. Vrhel

Novel structural features of bovine papillomavirus capsid revealed by a three-dimensional reconstruction to 9 Å resolution

The three-dimensional structure of bovine papillomavirus has been determined to 9 Å resolution by reconstruction of high resolution, low dose cryo-electron micrographs of quench-f rozen virions. Although hexavalent and pentavalent capsomeres form star-shaped pentamers of the major capsid protein L1, they have distinct high-resolution structures. Most prominently, a 25 Å hole in the centre of hexavalent capsomeres is occluded in the pentavalent capsomeres. This raises the possibility that the L2 minor capsid protein is located in the centre of the pentavalent capsomeres. Inter-capsomere connections ∼10 Å in diameter were clearly resolved. These link adjacent capsomeres and are reminiscent of the helical connections that stabilize polyomavirus.

Color image processing [basics and special issue overview]

umans have always seen the world in color but only recently have we been able to generate vast quantities of color images with such ease. In the last three decades, we have seen a rapid and enormous transition from grayscale images to color ones. Today, we are exposed to color images on a daily basis in print, photographs, television, computer displays, and cinema movies, where color now plays a vital role in the advertising and dissemination of information throughout the world. Color monitors, printers, and copiers now dominate the office and home environments, with color becoming increasingly cheaper and easier to generate and reproduce. Color demands have soared in the marketplace and are projected to do so for years to come. With this rapid progression, color and multispectral properties of images are becoming increasingly crucial to the field of image processing, often extending and/or replacing previously known grayscale techniques. We have seen the birth of color algorithms that range from direct extensions of grayscale ones, where images are treated as three monochrome separations, to more sophisticated approaches that exploit the correlations among the color bands, yielding more accurate results. Hence, it is becoming increasingly necessary for the signal processing community to understand the fundamental differences between color and grayscale imaging. There are more than a few extensions of concepts

Optimal nonnegative color scanning filters

In this correspondence, the problem of designing color scanning filters for multi-illuminant color recording is considered. The filter transmittances are determined from a minimum-mean-squared orthogonal tristimulus error criterion that minimizes the color error in estimates obtained from noisy recorded data. Nonnegativity constraints essential for physical realizability are imposed on the filter transmittances. In order to demonstrate the significant improvements obtained, the resulting filters are compared with suboptimal filters reported in earlier literature.

Design and realization of optimal color filters for multi-illuminant color correction

A method of selecting optimal color filters to perform accurate multi-illuminant color correction is reviewed. The transmittances for a set of filters obtained by the method were provided to a color filter manufacturer. The manufacturer used a dichroic filter modeling program to produce transmittances that satisfied the physical constraints of the manufacturing process and approximated the optimal filter transmittances. The ideal and manufacturable filters are compared through computer simulation and their accuracy assessed during the CIE Δ E L*a*b measure. The results show that the unconventional shapes of the optimal filters can be weil approximated by actual filters with slight degradation in performance.

Rapid computation of the continuous wavelet transform by oblique projections

We introduce a fast simple method for computing the real continuous wavelet transform (CWT). The approach has the following attractive features: it achieves O(N) complexity per scale, the filter coefficients can be analytically obtained by a simple integration, and the algorithm is faster than a least squares approach with negligible loss in accuracy. Our method is to use P wavelets per octave and to approximate them with their oblique projection onto a space defined by a compactly supported scaling function. The wavelet templates are expanded to larger sizes (octaves) using the two-scale relation and zero-padded filtering. Error bounds are presented to justify the use of an oblique projection over an orthogonal one. All the filters are FIR with the exception of one filter, which is implemented using a fast recursive algorithm.

Color scanner calibration via a neural network

The mathematical formulation of calibrating color scanners is presented. The mapping from scanned values to colorimetric values is inherently nonlinear. Calibration required approximating this nonlinear mapping. Neural networks are particularly suited to this task. Performance using an artificial neural network generated LUT is compared to that achieved by other commonly used methods.

Projection based prefiltering for multiwavelet transforms

We introduce a method for initializing the multiwavelet decomposition algorithm. The initialization procedure is the orthogonal projection of the input signal into the space defined by the multiscaling function. The approach will always have a solution, places no restrictions on the input (except that it be contained within L/sub 2/), and can be implemented in a fast algorithm. We present the details of our approach and compare it with another proposed method of prefiltering.

Color image resolution conversion

In this paper, we look at the problem of spatially scaling color images. We focus on an approach that takes advantage of the human visual systems color spatial frequency sensitivity. The algorithm performs an efficient least-squares (LS) resolution conversion for the luminance channel and a low-complexity pixel replication/reduction in the chrominance channels. The performance of the algorithm is compared to a LS method in sRGB and CIELAB color spaces, as well as standard bilinear interpolation in sRGB space. The comparisons are made in terms of computational cost and color error in sCIELAB.

Fast continuous wavelet transform: a least-squares formulation

Abstract We introduce a general framework for the efficient computation of the real continuous wavelet transform (CWT) using a filter bank. The method allows arbitrary sampling along the scale axis, and achieves O( N ) complexity per scale where N is the length of the signal. Previous algorithms that calculated non-dyadic samples along the scale axis had O( N log( N )) computations per scale. Our approach approximates the analyzing wavelet by its orthogonal projection (least-squares solution) onto a space defined by a compactly supported scaling function. We discuss the theory which uses a duality principle and recursive digital filtering for rapid calculation of the CWT. We derive error bounds on the wavelet approximation and show how to obtain any desired level of accuracy through the use of longer filters. Finally, we present examples of implementation for real symmetric and anti-symmetric wavelets.

Multi-channel restoration of electron micrographs

We introduce a projection based multi-channel restoration method which is useful in cases for which there is no a priori information about the input signal. The method is especially helpful in situations where a large number of specimens are later combined to achieve additional noise reduction. We describe the approach and discuss the problem of restoring electron micrographs. The method does require knowledge of the impulse response of the degradation. For this reason, the sensitivity of the approach to uncertainty in this degradation is investigated through simulation.