Showing papers by "Gaurav Sharma published in 1997"
TL;DR: Fundamental concepts of color perception and measurement are first presented using vector-space notation and terminology in order to establish the background and lay down terminology.
Abstract: This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented using vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided.
534 citations
TL;DR: An extension of the most promising measure, based on linearized CIELAB space, is proposed to obtain a new figure of merit that has a high degree of perceptual relevance and also accounts for the varying noise performance of different filters.
Abstract: In the design and evaluation of color scanners and cameras, it is useful to have a single figure of merit that closely agrees with perceived color accuracy. In the past, several measures of goodness for color scanning filters have been proposed to fulfil such a requirement. Most of the proposed measures have had shortcomings in that they are either based on error metrics in color spaces that are not perceptually uniform, or in that they do not take into account the effects of measurement noise. An extension of the most promising measure, based on linearized CIELAB space, is proposed to obtain a new figure of merit that has a high degree of perceptual relevance and also accounts for the varying noise performance of different filters. The paper also provides a common framework for the different figures of merit and a comprehensive comparison of their computational complexity and reliability.
126 citations
TL;DR: In this correspondence, two new sets motivated by total least squares are introduced for set theoretic estimation and the convexity of these sets is established and the projection operators onto these sets are given.
Abstract: The restoration of a signal degraded by a stochastic impulse response is formulated as a problem with uncertainties in both the measurements and the impulse response. The method of total least squares, and variants thereof, are effective techniques for solving this class of problems. However, unlike set theoretic estimation schemes, these methods do not allow the incorporation of other a priori information in the estimate. In this correspondence, two new sets motivated by total least squares are introduced for set theoretic estimation. The convexity of these sets is established and the projection operators onto these sets are given. Through simulations, the advantages of the new technique over conventional and older set theoretic schemes for restoration are demonstrated.
17 citations