enfuse(1)enfuse(1)NAMEenfuse - poor man's HDR
SYNOPSISenfuse [OPTIONS] -o OUTPUT INPUT...
DESCRIPTION
Enfuse merges overlapping images using the Mertens-Kautz-Van Reeth
exposure fusion algorithm. This is a quick way to blend differently
exposed images into a nice output image, without producing intermediate
HDR images that are then tonemapped to a viewable image. This simpli‐
fied process often works much better than the currently known tonemap‐
ping algorithms.
Enfuse can also be used to build extended DOF images by blending a
focus stack.
The basic idea is that pixels in the input images are weighted accord‐
ing to qualities such as proper exposure, good contrast, and high satu‐
ration. These weights determine how much a given pixel will contribute
to the final image. A Burt & Adelson multiresolution spline blender is
used to combine the images according to the weights. The multiresolu‐
tion blending ensures that transitions between regions where different
images contribute are difficult to see.
Enfuse uses three different criteria to judge the quality of a pixel:
exposure, saturation, and contrast. The exposure criteria favors pix‐
els with luminance close to the middle of the range. These pixels are
considered better-exposed than those with high or low luminance levels.
The saturation criteria favors highly-saturated pixels. The contrast
criteria favors high-contrast pixels. Enfuse can use standard devia‐
tion or Laplacian magnitude or a blend of both as local contrast mea‐
sure.
You can adjust how much importance is given to each criteria by setting
the weight parameters on the command line. For example, if you set
--wExposure=1.0 and --wSaturation=0.5, Enfuse will favor well-exposed
pixels over highly-saturated pixels when blending the source images.
The impact of these parameters on the final result will not always be
clear. The quality of the result is subject to your artistic interpre‐
tation. Playing with the weights may or may not give you a more pleas‐
ing result. I encourage you to experiment (perhaps using downsized
images for speed).
Enfuse expects each input image to have an alpha channel. By setting
the alpha values of pixels to zero, users can manually remove those
pixels from consideration when blending. If an input image lacks an
alpha channel, Enfuse will print a warning and continue assuming all
pixels should contribute to the final output. Any alpha value other
than zero is interpreted as "this pixel should contribute to the final
image".
COMMON OPTIONS-h Print information on the available options.
-l LEVELS
Use exactly this many LEVELS for pyramid blending. This trades
off quality of results for faster execution time and lower mem‐
ory usage. The default is to use as many levels as possible
given the size of the overlap region. Enfuse may still use a
smaller number of levels if the geometry of the images demands
it.
-o OUTPUT-FILE
Required option. Specify the name of the OUTPUT-FILE.
-v Verbose output.
-w Blend around the -180/+180 degrees boundary. Useful for
full-360 degrees panoramas. Enfuse currently does not blend the
zenith or the nadir, so you may still see some seams in these
areas.
--compression=COMP
Write a compressed output file. Valid values for COMP are NONE,
PACKBITS, LZW and DEFLATE for TIFF files, and numbers from 0-100
for JPEG files.
-z Use LZW compression for the output image.
EXTENDED OPTIONS-b BLOCKSIZE
Set the BLOCKSIZE in Kilobytes for Enfuse's image cache. This
is the amount of data that Enfuse will move to and from the disk
in one go. The default is 2048KB, which should be ok for most
systems.
-c Use the CIECAM02 color appearance model for blending colors.
Your input TIFF files should have embedded ICC profiles. If no
ICC profile is present, Enfuse will assume that image uses the
sRGB color space. The difference between using this option and
Enfuse's default color blending algorithm is very slight, and
will be most noticeable when you need to blend areas of differ‐
ent primary colors together.
-g Gimp (ver. < 2) and Cinepaint exhibit unusual behavior when
loading images with unassociated alpha channels. Use the -g
flag to work around this. With this flag Enfuse will create the
output image with the associated alpha tag set, even though the
image is really unassociated alpha.
-f WIDTHxHEIGHT[+xXOFFSET+yYOFFSET]
Set the size of the output image manually. This is useful when
the input images are cropped TIFF files, such as those produced
by Nona.
-m CACHESIZE
Set the CACHESIZE in megabytes of Enfuse's image cache. This is
the amount of memory Enfuse will use for storing image data
before swapping to disk. The default is 1024MB.
FUSION OPTIONS
--wExposure=WEIGHT
Sets the relative WEIGHT of the well-exposedness criteria.
Increasing this weight relative to the others will make well-
exposed pixels contribute more to the final output. Valid
range: 0 <= WEIGHT <= 1.
--wMu=MEAN
Set the mean (center) of the Gaussian exposure weight curve.
Default: 0.5, this gives pixels with value 128 (when using 8 bit
images) the highest weight. Valid range: 0 <= MEAN <= 1.
--wSigma=STDDEV
Standard deviation STDDEV of the Gaussian exposure weight curve.
Default: 0.2. Low numbers give less weight to pixels that are
far from --wMu. Valid range: 0 <= STDDEV <= 10.
--wSaturation=WEIGHT
Sets the relative weight of high-saturation pixels. Increasing
this weight makes pixels with high saturation contribute more to
the final output. Valid range: 0 <= WEIGHT <= 1.
--wContrast=WEIGHT
Sets the relative weight of high-contrast pixels. Valid range:
0 <= WEIGHT <= 1.
--HardMask
Force hard blend masks on the finest scale. This avoids averag‐
ing of fine details (only), at the expense of increasing the
noise. This improves the sharpness of focus stacks consider‐
ably.
EXPERT OPTIONS
--ContrastWindowSize=SIZE
Window SIZE for local contrast analysis. Values larger than 5
might result in a blurry composite and increased computation
times. Values in the range of 3 to 5 have given good results on
focus stacks. Valid range: SIZE >= 3.
--GrayProjector=PROJ
Use gray projector PROJ for conversion of RGB-images to
grayscale masks. Valid values for PROJ are:
"average" - Average red, green, and blue channel with equal
weights. This is the default and it often is a good projector
for gamma=1 data. Y = (R + G + B) / 3
"l-star" - Use the L*-channel of the L*a*b*-conversion of the
image as its grayscale representation. This is a useful projec‐
tor for gamma=1 data. It reveals minute contrast variations
even in the shadows and the highlights. This projector is com‐
putationally expensive.
"lightness" - Compute the lightness of each RGB-pixel as in an
HSL-conversion of the image. Y = (max(R, G, B) + min(R, G, B))
/ 2
"value" - Take the Value-channel of the HSV-conversion of the
image. Y = max(R, G, B)
"luminance" - Use the weighted average of the RGB pixel's chan‐
nels as defined by CIE and the JPEG standard. Y = 0.30 * R +
0.59 * G + 0.11 * B
"channel-mixer:RED-WEIGHT:GREEN-WEIGHT:BLUE-WEIGHT" - Weight the
channels as given. Y = RED-WEIGHT * R + GREEN-WEIGHT * G +
BLUE-WEIGHT * B
The weights are automatically normalized to one, so
--GrayProjector=channel-mixer:0.25:0.5:0.25
--GrayProjector=channel-mixer:1:2:1
--GrayProjector=channel-mixer:25:50:25
all define the same mixer configuration.
The three weights RED-WEIGHT, GREEN-WEIGHT, and BLUE-WEIGHT
define the relative weight of the respective color channel. The
sum of all weights is normalized to one. Default: average.
--EdgeScale=EDGESCALE[:LCESCALE[:LCEFACTOR]]
A non-zero value for EDGESCALE switches on the Laplacian-of-
Gaussian (LoG) edge detection algorithm. EDGESCALE is the
radius of the Gaussian used in the search for edges. Default: 0
pixels.
A positive LCESCALE turns on local contrast enhancement (LCE)
prior to the LoG edge detection. LCESCALE is the radius of the
Gaussian used in the enhancement step, LCEFACTOR is the weight
factor ("strength").
enhanced := (1 + LCEFACTOR) * original - LCEFACTOR * GaussianS‐
mooth(original, LCESCALE)
LCESCALE defaults to 0 pixels and LCEFACTOR defaults to 0.
Append "%" to LCESCALE to specify the radius as a precentage of
EDGESCALE. Append "%" to LCEFACTOR to specify the weight as a
percentage.
--MinCurvature
Define the minimum curvature for the LoG edge detection.
Default: 0. Append a "%" to specify the minimum curvature rela‐
tive to maximum pixel value in the source image (e.g. 255 or
65535).
A positive value lets Enfuse use the local contrast data (--Con‐
trastWindowSize) for curvatures less than MC and LoG data for
values above it.
A negative value truncates all curvatures less than -MC to zero.
Values above MC are left unchanged. This effectively suppresses
weak edges.
EXAMPLES
To blend an exposure stack given in files exposure_01.tif, expo‐
sure_02.tif, ...
enfuse-o result.tif exposure_*.tif
To blend a focus stack to form an extended depth of field image set the
contrast weight to 1 and use very low values for exposure and satura‐
tion criteria to get meaningful results in low contrast areas.
enfuse-o result.tif --wExposure=0.001 --wSaturation=0.001 --wCon‐
trast=1 --HardMask focus_*.tif
For additional information on blending focus stacks, including usage of
the expert options, refer to the enfuse-focus-stacking texinfo file.
AUTHORS
Andrew Mihal <acmihal@users.sourceforge.net>. Thanks to Simon Andriot
and Pablo Joubert for suggesting the Mertens-Kautz-Van Reeth technique
and the name "Enfuse". The contrast criteria has been added by Pablo
d'Angelo <dangelo@users.sourceforge.net> Dr. Christoph L. Spiel added
the gray projectors and the LoG-based edge detection.
September 8, 2008 enfuse(1)
