737 research outputs found
Navigating the roadblocks to spectral color reproduction: data-efficient multi-channel imaging and spectral color management
Commercialization of spectral imaging for color reproduction will require the identification and traversal of roadblocks to its success. Among the drawbacks associated with spectral reproduction is a tremendous increase in data capture bandwidth and processing throughput. Methods are proposed for attenuating these increases with data-efficient methods based on adaptive multi-channel visible-spectrum capture and with low-dimensional approaches to spectral color management. First, concepts of adaptive spectral capture are explored. Current spectral imaging approaches require tens of camera channels although previous research has shown that five to nine channels can be sufficient for scenes limited to pre-characterized spectra. New camera systems are proposed and evaluated that incorporate adaptive features reducing capture demands to a similar few channels with the advantage that a priori information about expected scenes is not needed at the time of system design. Second, proposals are made to address problems arising from the significant increase in dimensionality within the image processing stage of a spectral image workflow. An Interim Connection Space (ICS) is proposed as a reduced dimensionality bottleneck in the processing workflow allowing support of spectral color management. In combination these investigations into data-efficient approaches improve two critical points in the spectral reproduction workflow: capture and processing. The progress reported here should help the color reproduction community appreciate that the route to data-efficient multi-channel visible spectrum imaging is passable and can be considered for many imaging modalities
Evaluation and improvement of the workflow of digital imaging of fine art reproduction in museums
Fine arts refer to a broad spectrum of art formats, ie~painting, calligraphy, photography, architecture, and so forth. Fine art reproductions are to create surrogates of the original artwork that are able to faithfully deliver the aesthetics and feelings of the original. Traditionally, reproductions of fine art are made in the form of catalogs, postcards or books by museums, libraries, archives, and so on (hereafter called museums for simplicity). With the widespread adoption of digital archiving in museums, more and more artwork is reproduced to be viewed on a display. For example, artwork collections are made available through museum websites and Google Art Project for art lovers to view on their own displays. In the thesis, we study the fine art reproduction of paintings in the form of soft copy viewed on displays by answering four questions: (1) what is the impact of the viewing condition and original on image quality evaluation? (2) can image quality be improved by avoiding visual editing in current workflows of fine art reproduction? (3) can lightweight spectral imaging be used for fine art reproduction? and (4) what is the performance of spectral reproductions compared with reproductions by current workflows? We started with evaluating the perceived image quality of fine art reproduction created by representative museums in the United States under controlled and uncontrolled environments with and without the presence of the original artwork. The experimental results suggest that the image quality is highly correlated with the color accuracy of the reproduction only when the original is present and the reproduction is evaluated on a characterized display. We then examined the workflows to create these reproductions, and found that current workflows rely heavily on visual editing and retouching (global and local color adjustments on the digital reproduction) to improve the color accuracy of the reproduction. Visual editing and retouching can be both time-consuming and subjective in nature (depending on experts\u27 own experience and understanding of the artwork) lowering the efficiency of artwork digitization considerably. We therefore propose to improve the workflow of fine art reproduction by (1) automating the process of visual editing and retouching in current workflows based on RGB acquisition systems and by (2) recovering the spectral reflectance of the painting with off-the-shelf equipment under commonly available lighting conditions. Finally, we studied the perceived image quality of reproductions created by current three-channel (RGB) workflows with those by spectral imaging and those based on an exemplar-based method
Combining transverse field detectors and color filter arrays to improve multispectral imaging systems
This work focuses on the improvement of a multispectral imaging sensor based on transverse field
detectors (TFDs). We aimed to achieve a higher color and spectral accuracy in the estimation of spectral
reflectances from sensor responses. Such an improvement was done by combining these recently developed
silicon-based sensors with color filter arrays (CFAs). Consequently, we sacrificed the filter-less full
spatial resolution property of TFDs to narrow down the spectrally broad sensitivities of these sensors.We
designed and performed several experiments to test the influence of different design features on the estimation
quality (type of sensor, tunability, interleaved polarization, use of CFAs, type of CFAs, number of
shots), some of which are exclusive to TFDs.We compared systems that use a TFD with systems that use
normal monochrome sensors, both combined with multispectral CFAs as well as common RGB filters
present in commercial digital color cameras. Results showed that a system that combines TFDs and
CFAs performs better than systems with the same type of multispectral CFA and other sensors, or even
the same TFDs combined with different kinds of filters used in common imaging systems. We propose
CFA+TFD-based systems with one or two shots, depending on the possibility of using longer capturing
times or not. Improved TFD systems thus emerge as an interesting possibility for multispectral acquisition,
which overcomes the limited accuracy found in previous studies.Spanish Ministry of
Economy and Competitiveness through the research
project DPI2011-2320
High-speed surface profilometry based on an adaptive microscope with axial chromatic encoding
An adaptive microscope with axial chromatic encoding is designed and developed, namely the AdaScope. With the ability to confocally address any locations within the measurement volume, the AdaScope provides the hardware foundation for a cascade measurement strategy to be developed, dramatically accelerating the speed of 3D confocal microscopy
Digital Color Imaging
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
us-ing 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
Non-parametric Methods for Automatic Exposure Control, Radiometric Calibration and Dynamic Range Compression
Imaging systems are essential to a wide range of modern day
applications. With the continuous advancement in imaging systems,
there is an on-going need to adapt and improve the imaging
pipeline running inside the imaging systems.
In this thesis, methods are presented to improve the imaging
pipeline of digital cameras. Here we present three methods to
improve important phases of the imaging process, which are (i)
``Automatic exposure adjustment'' (ii) ``Radiometric
calibration'' (iii) ''High dynamic range compression''. These
contributions touch the initial, intermediate and final stages of
imaging pipeline of digital cameras.
For exposure control, we propose two methods. The first makes use
of CCD-based equations to formulate the exposure control problem.
To estimate the exposure time, an initial image was acquired for
each wavelength channel to which contrast adjustment techniques
were applied. This helps to recover a reference cumulative
distribution function of image brightness at each channel. The
second method proposed for automatic exposure control is an
iterative method applicable for a broad range of imaging systems.
It uses spectral sensitivity functions such as the photopic
response functions for the generation of a spectral power image
of the captured scene. A target image is then generated using the
spectral power image by applying histogram equalization. The
exposure time is hence calculated iteratively by minimizing the
squared difference between target and the current spectral power
image. Here we further analyze the method by performing its
stability and controllability analysis using a state space
representation used in control theory. The applicability of the
proposed method for exposure time calculation was shown on real
world scenes using cameras with varying architectures.
Radiometric calibration is the estimate of the non-linear mapping
of the input radiance map to the output brightness values. The
radiometric mapping is represented by the camera response
function with which the radiance map of the scene is estimated.
Our radiometric calibration method employs an L1 cost function by
taking advantage of Weisfeld optimization scheme. The proposed
calibration works with multiple input images of the scene with
varying exposure. It can also perform calibration using a single
input with few constraints. The proposed method outperforms,
quantitatively and qualitatively, various alternative methods
found in the literature of radiometric calibration.
Finally, to realistically represent the estimated radiance maps
on low dynamic range display (LDR) devices, we propose a method
for dynamic range compression. Radiance maps generally have
higher dynamic range (HDR) as compared to the widely used display
devices. Thus, for display purposes, dynamic range compression is
required on HDR images. Our proposed method generates few LDR
images from the HDR radiance map by clipping its values at
different exposures. Using contrast information of each LDR
image generated, the method uses an energy minimization approach
to estimate the probability map of each LDR image. These
probability maps are then used as label set to form final
compressed dynamic range image for the display device. The
results of our method were compared qualitatively and
quantitatively with those produced by widely cited and
professionally used methods
- …