Imaging Spectroscopy (IS) is a promising tool for studying soil properties in large spatial domains. Going from point to image spectrometry is not only a journey from micro to macro scales, but also a long stage where problems such as dealing with data having a low signal-to-noise level, contamination of the atmosphere, large data sets, the BRDF effect and more are often encountered. In this paper we provide an up-to-date overview of some of the case studies that have used IS technology for soil science applications. Besides a brief discussion on the advantages and disadvantages of IS for studying soils, the following cases are comprehensively discussed: soil degradation (salinity, erosion, and deposition), soil mapping and classification, soil genesis and formation, soil contamination, soil water content, and soil swelling. We review these case studies and suggest that the 15 data be provided to the end-users as real reflectance and not as raw data and with better signal-to-noise ratios than presently exist. This is because converting the raw data into reflectance is a complicated stage that requires experience, knowledge, and specific infrastructures not available to many users, whereas quantitative spectral models require good quality data. These limitations serve as a barrier that impedes potential end-users...
The Cassini Imaging Science Subsystem acquired high-resolution imaging data on the outer Saturnian moon, Phoebe, during Cassini's close flyby on 11 June 2004 and on Iapetus during a flyby on 31 December 2004. Phoebe has a heavily cratered and ancient surface, shows evidence of ice near the surface, has distinct layering of different materials, and has a mean density that is indicative of an ice-rock mixture. Iapetus's dark leading side (Cassini Regio) is ancient, heavily cratered terrain bisected by an equatorial ridge system that reaches 20 kilometers relief. Local albedo variations within and bordering Cassini Regio suggest mass wasting of ballistically deposited material, the origin of which remains unknown.
The Digital Imaging Remote Sensing Image Generation (DIRSIG)
model is a synthetic image generation (SIG) tool developed by the Digital
Imaging/Remote Sensing (DIRS) group at Rochester Institute of Technology's
(RIT) Center for Imaging Science (CIS). Validation of a series of DIRSIG
scenes over a broad spectral range has been presented. The validation
scenario makes use of airborne and ground truth data collected during the
Western Rainbow study conducted from October 18 24, 1995 at the United
States Army Proving Ground in Yuma, Arizona. Three sensors were simulated
in the validation scenario: the Daedalus multispectral sensor, the
Hyperspectral Digital Imagery Collection Experiment (HYDICE), and the
Spatially Enhanced Broadband Array Spectrograph System (SEBASS), and
collectively, they covered the spectrum from 0.4 to 14 microns.
As part of the study, various emissivity extraction techniques have
been reviewed, and DIRSIG's potential as an imaging spectroscopy tool in the
8 to 14 |a,m atmospheric window has been evaluated. One procedure: the
Planck curve fitting technique, has been implemented and utilized with
DIRSIG, SEBASS and ground truth data to extract emissivity spectra.
Mobile imaging helps realize "any time, anywhere" visual communication by allowing consumers to capture, review, share, and print pictures via mobile devices while "on the go". However, major technical challenges exist in bandwidth, power consumption, display and other areas. As a result, the limited resources available in mobile imaging need to be utilized in an intelligent and effective fashion. To this end, we propose to use emphasis image selection (EIS), which automatically selects the most important image, i.e., the one that should receive the most attention or special treatment, given a set of photographic images that typically belong to the same event.
Images from a film photofinishing order or a digital camera memory card are first clustered into groups related to different events based on metadata and image content. Emphasis images are selected to provide a summary of the group content and are sent to mobile devices for preview, sharing, browsing, and printing. Emphasis images also receive favorable treatment in image rendering, compression and transmission. Experimental results using consumer pictures are presented to demonstrate the efficacy of the proposed system.; "Efficient mobile imaging using emphasis image selection...
A generalized imaging system geometric model has been incorporated into the
Center for Imaging Science Digital Imaging and Remote Sensing Image
Generation (DIRSIG) software system. The camera model is capable of
simulating the geometric characteristics of frame cameras, line scanners and
pushbroom scanners. The user of the model has the ability to define both the
sensor internal orientation as well as provide time varying external orientation
parameters. The model has been successfully validated through the use of both
diagnostic simulated scenes as well as quantitative comparisons between
actual imagery and simulated imagery.
An image quality investigation of visible spectral imaging systems was performed. Spectral images were simulated using differ-ent combinations of imaging system parameters with different numbers of imaging channels, wavelength steps, and noise levels based on two practical spectral imaging systems. A mean opinion score ( MOS) was determined from a subjective visual assess-ment scale experiment for image quality of spectral images, rendered to a three- channel LCD display. A set of image distortion measures, including color difference for color images, were defined based on image quality concerns. The relationships between the distortion factors and the combinations of parameters in spectral imaging systems are discussed in detail. The MOS values and distortion measures were highly correlated. The results indicate that the image quality of spectral imaging systems was significantly affected by the number of channels used with noise in the image capture stage. The selection of wavelength steps had no significant impact on final image quality, especially when there was no noise involved. The results also showed that the contrast factor indicates a different impact on image quality for human portraits compared to other relatively complex scene images. An empirical metric is proposed to estimate the scaled image quality. The correlation between this metric and the subjec-tive measure...
Spectral imaging has been widely developed over the last ten
years for archiving cultural heritage. It can retrieve spectral
reflectance of each scene pixel and provide the possibility to
render images for any viewing condition. A new spectral
reconstruction method, the matrix R method, can achieve high
spectral and colorimetric accuracies simultaneously for a specific
viewing condition. Although the matrix R method is very effective,
the reconstructed reflectance spectrum is not smooth when
compared with in situ spectrophotometry. The goal of this
research was to smooth the spectrum and make it more accurate.
One possible solution is to identify pigments and find their
compositions for each pixel. After that, the reflectance spectrum
can be modified based on two-constant Kubelka-Munk theory
using the absorption and scattering coefficients of these pigments,
weighted by their concentrations. The concentrations were
optimized to best fit the spectral reflectance predicted by the
matrix R method. As a preliminary experiment, it was assumed
that a custom target was painted using several known pigments.
The simulation results show that incorporating pigment mapping
into the matrix R method can recover the smoothness of the
The accuracy of color image-acquisition systems is most
often evaluated using test targets of uniform color patches
imaged under optimal conditions. In artwork imaging,
system performance is judged visually, comparing the art
with images rendered for display or print. Because the
surface properties of the art may not be uniform, the
spectral properties of the pigments may be different than the
test targets, the sizes may be different, renderings are often
metameric to the art, taking and viewing lighting geometries
may be different, and the museum observers are more
experienced than scientists in judging color accuracy
visually, color accuracy as determined on a visual basis may
be quite different than target performance. Therefore, an
experiment was performed where a spectral-imaging
system, designed for scientific purposes under laboratory
conditions, was taken to a museum and tested in its
photographic and conservation departments. The work of
art evaluated was Henri Matisse’s Pot of Geraniums.
Spectral and colorimetric comparisons were made between
in situ small aperture spectrophotometry and imaging. The
average performance was 3.7ΔE00 and 3.1% spectral RMS;
this was similar to an independent verification target of
typical artist pigments applied to a canvas board. Viewed in
Data projectors are often used in demanding imaging applications requiring accurate color. To properly control the color output of such a device, one needs accurate color control models. This paper will describe a color management algorithm for a four-color DLP projector.
Four-channel color displays have only recently been introduced to the market. The displays being examined in this paper have the traditional red, green and blue channels and also a supplemental white channel. In parallel to the four-color printer problem, a fourth channel in a display creates a color reproduction challenge since one XYZ can potentially be mapped to many RGBW combinations. A further complication of these projectors is that at the computer interface they are treated as RGB displays. The conversion from RGB to RGBW takes place internally making them at once compatible with current RGB display signals and yet unfriendly to simple color management approaches.
The characterization of a display forms the foundation of a mapping from device digital coordinates to colorimetry. This is referred to as the “ forward model.” A common method for characterizing typical RGB color displays starts with three one-dimensional input look-up tables (LUTs) for linearizing the digital input signals with respect to tristimulus values (XYZ). This is followed by a 3x3 matrix for scalar rotation...
The widespread use of data projectors in more demanding imaging applications has emphasized the need for accurate methods of their color control. Projectors are relied upon in settings where color reproduction is increasingly important, such as digital cinema, and business applications including advertising and presentations using such color-critical items as corporate logos. We have measured and characterized a set of such data projectors, using both liquid crystal display (LCD) and Digital Light ProcessingTM display technologies. (DLPTM, trademarked Texas Instruments.) LCD projectors are successfully modeled using established techniques for LCD projectors and display screens as typically found in laptop computers. For the DLP devices, the LCD model is extended using a previously-proposed model in combination with a new method for calculating the amount of white channel addition. Colorimetric results are presented for both types of display technology for a series of projectors, with the more complex DLP modeling performing as well as the simpler LCD modeling.; "Colorimetric characterization model for DLP projectors," Proceedings of the Eleventh Color Imaging Conference: Color Science and Engineering Systems, Technologies, Applications. The Society for Imaging Science and Technology. Held in Scottsdale...
Recent developments in spectral imaging are pointing
toward a future where the demands on color management
will require a richer infrastructure than that which is
currently offered. ICC color management includes a stage
where all colors are transformed to and from XYZ-based
colorspaces. This colorimetric bottleneck is acceptable
within a metameric or Maxwellian approach to color
reproduction, but severely undermines the advantages of
spectral imaging. Spectralizer, a spectral image
visualization tool, has been implemented to provide a
platform where spectral images may be easily displayed,
manipulated, analyzed and processed. It has proven to be
useful in investigating algorithms and prototype datastructures
for performing the management of color within a
spectral imaging environment.; "Color management within a spectral image visualization tool," Proceedings of the Eighth Color Imaging Conference: Color Science and Engineering Systems, Technologies, Applications. The Society for Imaging Science and Technology. Held in Scottsdale, Arizona: 2000. The article may be accessed on Mark Fairchild's website at http://www.cis.rit.edu/fairchild/PDFs/PRO10.pdf or on the publisher's website (additional feels may apply) at http://www.imaging.org/store/epub.cfm?abstrid=3254; RIT community members may access full-text via RIT Libraries licensed databases: http://library.rit.edu/databases/; n/a