Many applications value an assessment of distorted natural images according to their usefulness, or utility, rather than their perceptual quality. For the quality task, human observers evaluate an image based on its perceptual resemblance to a reference, whereas for the utility task, the usefulness of an image as a surrogate for a reference is under evaluation. This paper presents a novel technique for acquiring perceived utility scores derived from textual descriptions produced by observers viewing images. The technique uses an observer-centric approach, so observers dictate the relevant concepts that characterize image usefulness. This technique is used to collect perceived utility (PU) scores for 150 distorted images that simulate scenes captured by a surveillance system. The capability of both the natural image contour evaluation (NICE) utility estimator, which compares contours of the reference and test images, and popular quality estimators to estimate PU is reported. The conclusions drawn from the results augment previously reported results and establish that a multi-scale implementation of NICE (MS-NICE) is the most robust utility estimator among the estimators evaluated, since MS-NICE consistently performs as well as estimators producing the most accurate perceived utility estimates for various distortion types.

In a print production system, the ability to match a printed document with its original electronic form enables services that improve robustness of the production process, such as content tracking mechanisms, or highly targeted quality assurance checks. One approach to this problem is to use overt markings that are later removed. This work, however, adopts a method that uses no markings, relying instead on fast image matching criteria. Though general image matching can be a difficult problem, constraints associated with the production environment allow construction of a simple, efficient solution to the matching problem. A reduced-reference quality assessment algorithm is presented that is used to match every document in a collection of printed and scanned documents with its original electronic form, based on down-sampling, equalization, quantization and per-pixel comparison. Using a 1085 image test set, a 100% matching rate is achievable by representing each image with only 5 bits-per-pixel at 8 dots-per-inch. The proposed method also compares favorably with other current reduced-reference quality assessment algorithms in terms of speed, storage and achieved matching rate.

In the quality assessment task, observers evaluate a natural image based on its perceptual resemblance to a reference. For the utility assessment task, observers evaluate the usefulness of a natural image as a surrogate for a reference. Humans generally use the information captured by an imaging system and tolerate distortions as long as the underlying task is performed reliably. Conventional notions of perceived quality cannot generally predict the perceived utility of a natural image. This paper examines variations to basic components of a recently introduced utility assessment algorithm that compares the contours of a reference and test image, referred to as the natural image contour evaluation (NICE), in terms of their capability to improve the prediction of perceived utility scores. Results show that classical edge-detection algorithms incorporated into NICE provide statistically equivalent performance to other, more complex edge-detection algorithms.

The structural similarity (SSIM) metric and its multi-scale extension (MS-SSIM) evaluate visual quality with a modified local measure of spatial correlation consisting of three components: mean, variance, and cross-correlation. This paper investigates how the SSIM components contribute to its quality evaluation of common image artifacts. The predictive performance of the individual components and pairwise component products is assessed using the LIVE image database. After a nonlinear mapping, the product of the variance and cross- correlation components yields nearly identical linear correlation with subjective ratings as the complete SSIM and MS- SSIM computations. A computationally simple alternative to SSIM (c.f Eq. (6)) that ignores the mean component and sets the local average patch values to 128 exhibits a 1% decrease in linear correlation with subjective ratings to 0.934 from the complete SSIM evaluation with an over 20% reduction in the number of multiplications.

While images often contain only one illumination source, objects in the scene are illuminated by varying intensities of that illuminant. We show that the illuminant can be estimated using a few known reflectances within an image taken with a hyperspectral camera. The method relies on projection to a non-convex constraint set, as well as to convex constraint sets. Simulations and tests on actual hyperspectral images show the method is effective.

Many signals and statistical distributions are a mixture of component signals or distributions. Current methods for estimating the proportion of each component assume a parametric form for the components. We introduce nonparametric methods, based on projections onto convex sets, to address the many practical cases where parametric models are not applicable. Comparisons are made with parametric methods and discussed for special cases where both methods can be used.

Pixels in hyperspectral images usually contain spectra from several classifiable objects, so that the recorded pixel is a mixture of the classes. Current methods estimate the proportion of each class using a set of spectral signatures describing only the class means. Since the means are known only by estimation methods, we introduce an approach that also incorporates the variation inherent in this estimation. The total least squares approach using projections onto convex sets (POCS) produces improved performance over simple maximum likelihood methods, even one that also uses the constraint sets and POCS.

The potential of incorporating electronically controlled photonic switching components in fiber-optic ring-based communication networks is explored. Possible extensions to fiber ring architectures with lithium niobate switches are proposed, and potential problems that limit wide-scale use of these devices are identified. The use of 2*2 directional couplers to provide faulty node bypass is investigated. This concept is extended to larger photonic switches with multiple fibers to provide higher throughput. This approach also provides multiple redundant paths that enable the network to be reconfigured based on traffic demands and faults on the ring. The concept of distributing switching capabilities among all the nodes in a network is introduced. Two networks with distributed switching capabilities are examined. Switching parameters that impact the application of photonic devices in ring networks are discussed.>