Imsense Ltd: The Pursuit of Perfect Photographs
Submitting Institution
University of East AngliaUnit of Assessment
Computer Science and InformaticsSummary Impact Type
TechnologicalResearch Subject Area(s)
Information and Computing Sciences: Artificial Intelligence and Image Processing
Medical and Health Sciences: Neurosciences
Psychology and Cognitive Sciences: Psychology
Summary of the impact
Research undertaken at UEA developed revolutionary algorithms for making
pictures look better. These algorithms were subsequently engineered into
prize winning desktop and embedded applications, resulting in the creation
of the spinout company, Imsense Ltd., in 2006.
In July 2010, Imsense Ltd. was acquired by [text removed for
publication] and the Imsense technology has now been incorporated into
[text removed for publication] product pipeline.
Underpinning research
The human visual system is quite remarkable: we see the details in the
shadow and the clouds in the sky simultaneously even though the clouds
might be thousands of times brighter. Yet, like digital images, the visual
system does not code the world directly. Indeed there are at most, 100
brightness levels coded in the visual cortex. How the eye achieves this
`dynamic' range compression (DRC) is not known but mimicking this ability
is essential to achieve the best looking photographs.
Prior art in DRC assumed that the dynamic range compression could be
solved by either adjusting brightness or contrast locally in an image.
Finlayson proposed that differently lit parts of the same scene conveyed
the same underlying information from the same physical surfaces but that
this information was, effectively, `coded' in different units [1].
Standardising the units naturally required both local contrast and local
brightness adjustments. Significantly, images recoded in standard units
have much smaller dynamic ranges and also look good with hitherto
invisible detail now apparent in images.
In common with other DRC approaches, the `local', spatially varying
computations implied by the Imsense method raised two important questions
[2]. First, how could the degree of `locality' be determined (evidently,
some images need more DRC than others). Finlayson observed that the local
filtering which was required could, equivalently, be cast as a problem of
differentiating an image, modulating the derivatives and then
reintegrating. In addition, Finlayson observed that very large brightness
edge—such as shadows—are uncommon and yet they dominate any procedure that
reintegrates the derivative field. In [3], the derivative field is
reintegrated in a way that is robust to the unexpected large edges by
using the tool of regularisation theory. Crucially, the degree of locality
required `falls out' from the underlying regularisation theory.
Secondly, how could the required spatial processing be implemented in a
way that avoided introducing spatial artefacts—such as haloing—into images
(as are commonly found in competing algorithms)? Robustness to spatial
artefacts is achieved by modelling the DRC computation as a provably
optimal spatially varying look up table operation [4].
Complementing the robust reintegration work, a novel approach to finding
differently illuminated regions (e.g. finding shadows) in an image was
developed by Finlayson and Fredembach [5]. Building on previous
commercially successful algorithms developed by Finlayson and Hordley [6],
Imsense Ltd. also developed leading algorithms for white-balance
leading to a patent by Finlayson and Trezzi.
Key Research Personnel:
Professor Graham Finlayson (UEA from 1999 to present)
Dr Barry Theobald (UEA Lecturer 2005 to present)
Dr Steven Hordley (UEA Postdoc and Lecturer, 1999 to 2006)
Dr Duan Jiang (UEA Fellow and Imsense employee, 2007)
Dr Francesc Tous (UEA summer intern 2004, 2005 and Imsense employee 2008
to 2010)
Dr Clement Fredembach (UEA PhD student 2003 to 2007)
Dr Elisabetta Trezzi (UEA PhD student 2003 to 2007)
References to the research
(UEA authors in bold)
Primary Publications
[2] G. Qiu, J. Duan and G.D. Finlayson
Learning to Display High Dynamic Range Images
Pattern Recognition 40 2641-2655 (2007)
doi: 10.1016/j.patcog.2007.02.012
This paper, as well as reviewing the field, extended the state of the
art in global tone curve adjustment (22 citations)
[5] G.D. Finlayson, S.D. Hordley and P.M. Hubel
Colour by Correlation: Unifying theories of colour constancy
IEEE transactions on Pattern Analysis and Machine Intelligence 23
1209-1221 (2001)
doi: 10.1109/34.969113
This paper develops a computational framework with respect to which
the majority of white point estimation algorithms can be cast (338
citations)
[6] G.D. Finlayson, C. Fredembach and M.S. Drew
Detecting Illumination in images
The International Conference on Computer Vision, Rio de Janeiro, 1-8,
(2007)
doi: 10.1109/ICCV.2007.4409089
Large dynamic range images typically have two or more illuminants
(e.g. sun and shadow) and so it is useful — using the algorithm
developed in this reference — to segment an image into regions lit by
different lights (16 citations)
According to the ISI Web of Knowledge, Pattern Recognition and IEEE PAMI
are respectively the 2nd and 47th ranked journals
(from the 463 listed) in the area of Computer Science (with impact factors
of 4.9 and 2.3 respectively). ICCV is the top conference in computer
vision and has an acceptance rate of less than 20%. All citations from
Google Scholar in September 2013.
Patents
[1] G.D. Finlayson
"Image Signal Processing"
WO/2004/051569 (2004) (copy of patent held on file at UEA)
[3] G.D. Finlayson
"Method and System for Generating Accented Image Data"
WO/2011/023969 (priority date 2010) (copy of patent held on file at UEA)
[4] G.D. Finlayson
"Method and System for Generating Enhanced Images"
WO/2011/101662 (priority date 2010) (copy of patent held on file at UEA)
Details of the impact
Imsense Ltd.: business and staff
The Intellectual Property which formed the core of the patent portfolio
underpinning Imsense Ltd. pipelined from Finlayson's `Colour Lab'
in the School of Computing Sciences at UEA. This portfolio included
patents covering dynamic range compression [1], fast algorithms [3,4] and
white balance. Imsense Ltd. was initially registered in 2006. It
was supported by Seedcorn funding of £200K from the ICENI Seedcorn fund (www.icenifund.com)
and raised venture capital from Braveheart Investment Group plc
(supporting statement [A]) and IQ capital (supporting statement [B]) in
two rounds of investment in 2008 and 2010. A significant portion of the
investment into Imsense Ltd. came from COIN (supporting
statement [C]): a regional `co-investment fund'. Like ICENI, this is an
`evergreen' fund whose remit is to invest in companies in the East-Anglian
region, with any returns reinvested into future regional projects.
At the end of 2010, Imsense Ltd. employed eight full time
equivalent members of staff. The company was initially based in Norwich
before moving to Cambridge in 2009. `Silicon Fen' as it is known, is the
network of Cambridge-based engineering and science-based companies which
thrive through the large number of co-located high-tech spin-outs and
their interactions.
Imsense Ltd. worked with local businesses such as N++ and Argon
design. N++ helped Imsense Ltd. develop its stand-alone PC
software `imphoto' (see supporting statement [D]), whilst Argon Design
helped assess the feasibility of implementing the Imsense technology on
dedicated hardware — a key requirement sought by many of Imsense Ltd.'s
potential customers (see supporting statement [E]).
Imsense Technology
Imsense Ltd. produced and sold software which had a wide impact in
the photographic world. Its popular [text removed for publication] App imphoto
attracted 100,000 downloads. Its Eye-Fidelity software was an
integral part of the OnOne Phototune software (see supporting press
release [F]) and Imsense stand-alone PC software was also available for
purchase on-line. In January 2010 the Imsense software was a winner of an
International Imaging Industry award (in the VISION 2020 competition) for
its Eye-Fidelity Dynamic Range Correction technology, particularly
as applied to real time video content processing (see supporting statement
[G]).
The Imsense processing software was well regarded by photographers,
including the internationally renowned photographer and author Michael
Freeman, who has stated publicly:
"I've just revisited some images I'd previously processed using high-end
photo-processing software. With imphoto I can get a more natural result in
a fraction of the time"
(see supporting statement [H])
Acquisition of Imsense Ltd. by [text removed for publication]
In 2010 Imsense Ltd. was acquired by [text removed for publication]
and the Imsense technology has now been incorporated into [text removed for publication] product pipeline (see supporting statement [I]) As a result
of the acquisition, investments made in Imsense Ltd. returned a
significant profit. The acquisition was also significant for the Imsense
Ltd. employees. For example, the Engineering Team have now been
working at [text removed for publication] for over two years.
On-going Collaboration
Following the Imsense Ltd. acquisition, [text removed for publication] established a four-year programme of collaboration with Prof
Finlayson and the School of Computing Sciences at UEA. This collaboration
has resulted in additional IPR, which is now being incorporated into new
products.
Sources to corroborate the impact
Venture Capital Funding for Imsense Ltd.
[A] Supporting statement from Braveheart Investment Group plc — a major
investor in Imsense Ltd. and observer on the management board
(letter held on file at UEA)
[B] Supporting statement from IQ Capital Partners — a major investor in Imsense
Ltd. and member of the management board
(letter held on file at UEA)
[C] Supporting statement from `COIN' — a regional co-investment fund —
confirming investment in Imsense Ltd.
(letter held on file at UEA)
Development of Imsense Products
[D] Supporting statement from N++ Ltd. confirming the provision of
engineering support for the development of the imphoto stand-alone
software
(letter held on file at UEA)
[E] Statement providing details of how Argon Design helped Imsense
Ltd. develop `on chip' versions of their software processing
technology
(letter held on file at UEA)
External Recognition for Imsense Products
[F] Press release from OnOne announcing the incorporation of Imsense
Ltd.'s Eye Fidelity software engine into their Photo tune
image processing software
(Downloaded from
http://www.ononesoftware.com/press/release.html?r=2009-10-27-1 on
6/6/13 and held on file at UEA)
[G] Press release from the International Imaging Industry Association
announcing a VISION 2020 award for Imsense Ltd.'s Eye Fidelity
video processing embedded software
(Downloaded from http://www.prweb.com/releases/Imaging/Computer_Vision/prweb3188924.htm
on 6/613 and held on file at UEA)
[H] Supporting statement by photographer Michael Freeman regarding his
use of imphoto (letter held on file at UEA)
Acquisition of Imsense Ltd. by [text removed for publication]
[I] Supporting statement from [text removed for publication] confirming the
acquisition of Imsense Ltd. in 2010 (letter held on file at UEA)