|
NOTE: Digital Imaging Ethics is
available as a 6 page Adobe Acrobat (PDF) document on our Handouts page.
Introduction to Image Editing Ethics

This
topic is increasingly on people's minds given that image manipulation "tricks" that
used to take considerable skill in a darkroom now can be done quite
easily by anyone using one of the powerful image editing programs that
are available. A user does not even have to be intentionally malicious
to alter an image in an unethical manner. Unfortunately, many users
are unaware of the issues or the effects of their actions.
Journalists have grappled with the credibility problems created by
altered images since the early days of photography (see: Faking
Images in Photojournalism). In western society a photograph is typically assumed
to be an accurate representation of reality, unless it is patently
obvious that it has been altered (e.g., SPY Magazine's cover photo
of a "pregnant" Bruce
Willis in September 1991). Most readers seem to understand and expect
that widely respected sources of information will adhere to a higher
standard of photojournalistic ethics than sources such as "tabloid
newspapers".
Scientists
are usually considered to be respected sources of information and there
is the understanding within the scientific community that data must not
be inappropriately manipulated or falsified. When this essay was first
composed in 2001, there were very few written guidelines for scientists.
Now some of the major professional societies have issued policy statements
regarding digital imaging, and many scientific journals have revamped
their instructions to authors to provide clearer guidance of how they
require images to be handled. Publications like the Journal of Cell Biology
have begun testing images in accepted articles to ensure compliance with
their guidelines and the Office of Research Integrity (HHS) has been
watching this issue closely.
In
this author’s experience the inappropriate manipulation of scientific
digital images typically does not arise from an intent to deceive or
to obscure information. More often the inappropriate manipulations are
simply due to ignorance of basic principles. It seemed to this author
that often what is needed is an explanation of why manipulations are
right or wrong. These twelve guidelines are an attempt to address this
issue. It should be noted that the author has extensive experience in
the microscopic imaging of biological specimens and these guidelines
reflect his personal experience in this field.
Guidelines
for the proper acquisition and manipulation of scientific digital
images:

- Scientific
digital images are data that can be compromised by inappropriate
manipulations.
Images are data arranged spatially in an XY matrix (or grid) and
each individual element (pixel) has a numerical value that represents
a grayscale or RGB intensity value. These data are a numerical sampling
of the specimen as presented by the data acquisition system (e.g.,
microscope) to the sensor (e.g., CCD camera). The data acquisition
system and sensor are subject to all the limitations and aberrations
that physics and instrument design may impose on the two devices.
To the observer's eye the image data may appear to accurately represent
what can be seen, however, it is the user's responsibility to understand
the limitations of the particular instrument.
| The
basic message is that humans are not very good observers,
that our vision system ignores a lot of information, that
having names and labels for recognized features is very important,
and that we often think we see what we expect to see. |
-
Dr. John Russ (1)
|
- Manipulation
of digital images should always be done on a copy of the
unprocessed image data file.
The
original raw data file is the standard to which the final image
can and should be compared. Maintaining a copy of the unaltered
original image is the user’s only protection against accusations
of misconduct. This is also the only way that users can recover
from a mistake in image processing. Data should be archived to
media that are not easily altered (e.g., CD-R or DVD-R) (2).
Maintaining the image in the original file format is highly recommended.
| Individual’s and corporations whose research falls
under the United States FDA’s “Final Rule on Electronic
Records and Electronic Signatures” (21 CFR part 11) have
mandatory requirements for maintaining the integrity of the
original image. This would include labs using “Good Lab
Practices”. Other industries where maintaining the original
image is required would include; forensics (rules of evidence)
and health care (liability, HIPAA). |
- Simple
adjustments to the entire image are usually acceptable.
This
would include techniques that are similar to standard darkroom
techniques (e.g., different contrast grades of paper, changes in
development time). With digital images this would include performing "reasonable" adjustments
of the levels and gamma settings. Because changes in gamma are
non-linear, many journals are requiring that these types of adjustments
be described in the figure legend or the methods section.
Small adjustments to the brightness and contrast are usually
acceptable, however, large adjustments are not recommended. This
is because it is very easy to truncate intensity information
in the image using brightness and contrast.
-
Cropping an image is usually acceptable.
Avoid acquisition bias. Capturing images that only confirm the lab’s “preferred
hypothesis” is a form of unethical cropping. Consider the following observation
by microscopy core facility director Dr. George McNamara.
| I suspect
that most published micrographs are "exemplary", "best
of", or, "the only one we took", or "the
only one that fit our hypothesis" (I call the latter two
categories, "N=1 experiments").
If you are putting together figures, and you select for
publication a micrograph based on any of these categories,
at least be honest to the reviewers and editor and say so
(hopefully they'll tell you to go back and collect data correctly
... even better, your coauthors should tell you ... best
of all, your inner super-ego should tell you).
What you should be publishing are representative micrographs.
That means you need to acquire sufficient images to document/quantify
the experiment. Your specimen and images should be good enough
that any of the micrographs can be used. In fact, if you
can only publish one micrograph per treatment group, use
a random number generator to pick which one...
|
- Dr. George McNamara (3) |
After
you have selected a specific image to use in a figure, what is your
motivation for cropping that image? Is it to improve the “composition” of
the image, or is it to hide something that disagrees with the hypothesis?
Remember
to leave yourself enough pixels so that the image will reproduce
well in a scientific journal. If you have to crop too much out,
it’s time to re-image your specimen. Don’t
let Photoshop replace good science.
-
Digital images that will be compared to one another should be
acquired under identical conditions, and any post-acquisition
image processing should also be identical.
Any processing of images that are to be compared should be identical,
especially if they will be published as a group of images in a single
figure. If there is a compelling reason that the images in a figure
were processed differently, this must be explained in the publication
or figure legend. Honesty is the best policy.
If background subtraction or white-level balancing (to compensate
for uneven illumination, etc) was performed, this should be acknowledged
in the methods section.
-
Manipulations that are specific to one area of an image and are
not performed on other areas are questionable.
This
would include techniques analogous to "dodging" and "burning" in
a photographic darkroom. This is a disputed issue. Purists would
state that selective enhancement should never be performed; however,
there are very rare occasions when it is legitimate to enhance a
specific area in an image.
Honesty
is the best policy. If portions of an image for publication were
selectively enhanced, the author should state it clearly in the
figure legend.
- Use of software filters to improve image quality is usually
not recommended for biological images.
Commercial software designed for desktop publishing cannot be counted
on to appropriately and scientifically manipulate the data in a digital
image. Digital image filters are typically mathematical functions
(convolution kernels) that change the numerical data in the pixels
in the image. If the filters are not used carefully, they may create
artifacts in an image that can lead to misinterpretation of the data.
If filters must be used, they should be noted in the figure legend
of published images. The note should include software version, specific
filters and any special settings that were used.
| Software
filters/Convolution kernel mask tutorial – Choose
the sharpening kernel, then press AUTO to start the tutorial.
Watch how the filter changes pixel values at every single pixel
and compare the before and after values in the small images. |
Software
filters and to some extent “cloning” (#8)
are sometimes used to clean up the background of an image. Scientists
must always remember the possibility that someone will look at
their data in a way they hadn’t considered. Perhaps the reader
will find that the collagen matrix, support media, interface between
two structures, or other “unimportant” features in
the image contains information that will spark an idea for their
research. If the author changes the “unimportant” things
to enhance the “important” things, they have lied to
the reader.
- Cloning or copying objects into a digital image, from other
parts of the same image or from a different image, is very questionable.
Users often consider using the technique of cloning sections of an
image to "clean up" a dirty preparation. If the image requires
this much processing, the best solution is to go back and take another
image from the sample or a new sample prepared under the same conditions.
The use of cloning techniques to create objects in an image that
did not exist there originally (e.g., "creating" a new
gel band) is completely unethical.
Use
of cloning and/or copying is asking for trouble. Most of the
falsified image cases that the Office of Research Integrity sees
use these techniques. Professional journals that closely examine
images (e.g., Journal of Cell Biology) can detect these sorts of
things pretty routinely.
Combining
images (e.g., two similar gels combined into one figure) is acceptable
at most journals only if it is clear to the editors & reviewers
that the two images are from separate sources. Often this means
a small gap between the two images or a black line that delineates
the two images. Scientifically, it is better to re-run the experiment,
rather than paste images together.
- Intensity
measurements should be performed on uniformly processed image
data, and the data should be calibrated to a known standard.
Be
aware that some instruments (e.g., fluorescence microscopes of
many types) are subject to a number of known fluctuations over
time as well as having other physics/electronics limitations. If
you are unaware of, or can’t account for, the limitations
of the acquisition instrument, you should not be performing intensity
measurements.
| Users of fluorescence microscopes should
read: The 39 Steps: A Cautionary Tale of Quantitative
Fluorescence (4), Seeing is believing?
A beginners’ guide to practical
pitfalls in image acquisition (5), and Multicolor
imaging: the important question of co-localization (6). |
-
Avoid the use of lossy compression.
There are very few good reasons to use the JPEG file format on scientific
digital images (other than displaying an image on a web page). JPEG
compression uses the discrete cosine function to reduce the file
size, however, it also changes the XY resolution of the image and
the intensity value of any given pixel.
If
you must use JPEG, perform the compression as the last thing
that is done to an image. With most image manipulation programs,
opening and saving a JPEG image multiple times runs the compression
algorithm on the image multiple times, further degrading the image
each time.
| …many
aspects of scientific and industrial usage involve subsequent
processing of a digital image, for example to enhance features
or count items. Using any form of lossy compression for images
in this context may create problems - after all the information
thrown away during lossy compression is generally that information
that is imperceptible to a human eye - not necessarily showing
the same characteristics as computer image processing software. |
- Joint Photographic Experts Group (JPEG) (7)
|
The reason for recording images in scientific studies
is not to keep remembrances of familiar objects and scenes,
but to record the unfamiliar. If it is not possible to
know beforehand what details may turn out to be important,
it is not wise to discard them. And if measurement of features
is contemplated (to measure size, shape, position or color
information), then lossy compression, which alters all of
those values, must be avoided.
|
- Dr. John Russ (1)
|
It is tempting to acquire your image files in JPEG format
to save disk space, but doing so compromises your data. Always
use TIF format.
|
- Journal of Cell Biology (8)
|
| Even with large scientific image formats the cost of storage
is vanishingly small. It, therefore, makes no sense not to
save an original unprocessed and uncompressed image file. The
MSA (Microscopy Society of America) format for this storage
is the TIFF file format.
|
-
J.M. MacKenzie, M.G. Burke, T. Carvalho & A. Eades
(2)
|
| JPEG image compression artifacts tutorial – Select
a sample image from the list. The two images should look virtually
the same. Now select the “difference image”, which
is the mathematical subtraction of the pixel intensities of
the JPEG image from the original. If the images were truly
identical, there would be no difference. The difference image
demonstrates that JPEG compression causes intensity information
to be spread out from its origin. |
| Important
- Users of the Adobe Acrobat writer
software should be aware that the default setting in this
program is to apply JPEG compression to any images embedded
in the document. These settings can be changed by the user. |
- Magnification
and resolution are important.
Digital images of real world objects sample an object
in a way such that each pixel in the image has a scale. This scale
may be in meters per pixel for satellite images or in tenths of microns
per pixel for microscope images. Ideally the scale is the same in
both the X and Y dimensions; however, this is not always the case.
The magnification of the image is determined by the difference between
the original scale of the pixel and the scale of the pixel in its
final form (e.g., paper printout, projected on the wall of a large
lecture hall). Since it is often impossible to know in advance what
the final magnification will be, a scale bar of known size is the
best way to express the magnification. Journals may resize your image,
so providing a numerical magnification number in a figure legend
may result in errors.
The ability of a microscope to resolve (separate two small, adjacent
objects) is limited by the wavelength of light used and the numerical
aperture of the objective lens (Rayleigh criterion).
| In most cases, to ensure adequate sampling for high-resolution
imaging, an interval of 2.5 to 3 samples for the smallest resolvable
feature is desirable. |
-
Spring, K.R., Russ, J.C., Parry-Hill, M.J., Fellers, T.J.,
Zuckerman, L.D. & Davidson (9) |
Note
that this statement means 2.5-3 samples (pixels) should be used
to capture the smallest resolvable features in each of the
three spatial dimensions (XYZ). Other dimensions, such as time and/or
wavelengths, should also be correctly sampled to avoid artifacts.
Undersampling (using too few pixels to describe a spatial feature
in a sample) can lead to artifacts masquerading as real structures.
Oversampling is not as problematic, however, it should be noted
that oversampling does not yield any additional spatial resolution
information from the specimen. In many types of fluorescence
microscopy oversampling may result in a loss of contrast (due
to limited amounts of light) and without contrast it is difficult
to resolve closely adjacent objects.
- Be
careful when changing the size (in pixels) of a digital image.
Changing
the size of an image (the number of pixels in X and Y) can introduce
resampling artifacts. Decreasing the image size (downsampling) can
cause the XY resolution in an image to be greatly reduced. If the size
reduction is not by a power of two, the software program has to be "creative" in
determining the intensity values of each pixel (guessing). Using a
power of two is slightly better, since this is a form of averaging,
and while the resolution is still decreased, it is decreased in a more
reproducible manner.
Increasing
the image size (upsampling) causes the software to interpolate
(guessing) to "create" pixels in between the existing
pixels. Upsampling an image does not increase the resolution,
in fact it may make it more difficult to resolve features because
of aliasing artifacts. In either case, users should insert a magnification
scale bar prior to resampling (magnification may be nearly impossible
to calculate afterwards).
Users should only change the total number of pixels in an image
one time to avoid compounding any artifacts that might be created.
| Adobe
Photoshop tip: If you are only changing the dpi of the image for different
output devices (e.g., printers), uncheck the resample image
box found at the bottom of the window that appears when invoking
the IMAGE|IMAGE SIZE menu item. By doing this you change the
scale of the image (72 dpi, 300 dpi, etc) without changing
the number of pixels in the width or height boxes. For more
information, see "Potentially
the most dangerous dialog box in Adobe Photoshop™". |
MSA position on Ethical Digital Imaging

At the 2003 summer council meeting of the Microscopy Society of America the following resolution was adopted as representing the position of the MSA on ethical digital image processing (as published in Microscopy Today Nov/Dec 2003, p61):
Ethical digital imaging requires that the original uncompressed image file be stored on archival media (e.g., CD-R) without any image manipulation or processing operation. All parameters of the production and acquisition of this file, as well as any subsequent processing steps, must be documented and reported to ensure reproducibility.
Generally, acceptable (non-reportable) imaging operations include gamma correction, histogram stretching, and brightness and contrast adjustments. All other operations (such as Unsharp-masking, Gaussian blur, etc.) must be directly identified by the author as part of the experimental methodology. However, for diffraction data or any other image data that is used for subsequent quantification, all imaging operations must be reported.
Journal
of Cell Biology - Instructions to Authors (2007)

From: http://www.jcb.org/misc/ifora.shtml
No specific feature within an image may be enhanced, obscured, moved, removed, or introduced. The grouping of images from different parts of the same gel, or from different gels, fields, or exposures must be made explicit by the arrangement of the figure (i.e., using dividing lines) and in the text of the figure legend. If dividing lines are not included, they will be added by our production department, and this may result in production delays. Adjustments of brightness, contrast, or color balance are acceptable if they are applied to the whole image and as long as they do not obscure, eliminate, or misrepresent any information present in the original, including backgrounds. Without any background information, it is not possible to see exactly how much of the original gel is actually shown. Non-linear adjustments (e.g., changes to gamma settings) must be disclosed in the figure legend. All digital images in manuscripts accepted for publication will be scrutinized by our production department for any indication of improper manipulation. Questions raised by the production department will be referred to the Editors, who will request the original data from the authors for comparison to the prepared figures. If the original data cannot be produced, the acceptance of the manuscript may be revoked. Cases of deliberate misrepresentation of data will result in revocation of acceptance, and will be reported to the corresponding author's home institution or funding agency.
See
also NATURE - Guide for Digital Images
| Note,
this document (Digital Imaging: Ethics) is an original work
of the author (Mr. Cromey). Endorsement by the Microscopy Society
of America, The Journal of Cell Biology, or any other persons
or institutions cited here should not be implied. |
Recommended
reading material (scientists)
*Note:
access to these articles may require a subscription
Additional
reading material (journalism)
- Phototruth
or Photofiction?, Thomas Wheeler, published by Lawrence Erlbaum
Associates, Mahwah, New Jersey, 2002.
- Ethics in the Age of Digital Photography, J. Long, (National Press Photographer's Association, September 1999)
- Photographs that lie: Welcome to journalism's newest ethical nightmare: digital enhancement, J.D. Lasica (Washington Journalism Review, June 1989)
- Photography
in the Age of Falsification, K. Brower, Atlantic Monthly, May 1998
(this content is now only available to subscribers)
- Every Picture can tell a Lie, D. Shenk, (Wired News, 1997)
- Ethics
in the Age of Digital Photography, J. Long, National
Press Photographer's Association, September 1999.
- Digital
Tampering in the Media, Politics and Law, Dartmouth University
References
*Note:
access to these articles may require a subscription
- Seeing
the Scientific Image (parts 1,2,3), John Russ, Proceedings
Royal Microscopy Society 39(2); 39(3); 39(4) (2004).
- Ethics
and Digital Imaging, J.M. MacKenzie, M.G. Burke, T.
Carvalho & A.
Eades. Microscopy Today 12:40-41. (2006)
- Crusade
for Publishing Better Light Micrographs – Light
Microscopy publication guidelines, George McNamara
- The
39 Steps: A Cautionary Tale of Quantitative 3-D Fluorescence Microscopy,
James Pawley, BioTechniques 28(5): 884-887 (2000).
- Seeing is
believing? A beginners’ guide to practical pitfalls
in image acquisition, Allison J. North, JCB 172(1): 9-18. (2006)
- Multicolor
imaging: the important question of co-localization, Anna Smallcombe,
Biotechniques 30, 1240-1242 (2001). free
registration required
- Scientific and
Industrial, Joint Photographic Experts Group
- The JCB
will let your data shine in RGB, Mike Rossner and Rob O’Donnell,
Journal of Cell Biology 164:11-13. (2004)
- Digital
Image Sampling Frequency, Spring, K.R., Russ, J.C., Parry-Hill,
M.J., Fellers, T.J., Zuckerman, L.D. & Davidson, M.W. (2006)
NOTE: Digital Imaging Ethics is
available as a 6 page Adobe Acrobat (PDF) document on our Handouts page.
|