Combining Multiple Images with Enblend 4.0-753b534c819d

Table of Contents


This manual is for Enblend (version 4.0-753b534c819d, 4 December 2009), a tool for compositing images in such a way that the seam between the images is invisible, or at least very difficult to see.

1 Overview

Enblend overlays multiple TIFF images using the Burt-Adelson multiresolution spline algorithm.1 This technique tries to make the seams between the input images invisible. The basic idea is that image features should be blended across a transition zone proportional in size to the spatial frequency of the features. For example, objects like trees and windowpanes have rapid changes in color. By blending these features in a narrow zone, you will not be able to see the seam because the eye already expects to see color changes at the edge of these features. Clouds and sky are the opposite. These features have to be blended across a wide transition zone because any sudden change in color will be immediately noticeable.

Enblend expects each input file to have an alpha channel. The alpha channel should indicate the region of the file that has valid image data. Enblend compares the alpha regions in the input files to find the areas where images overlap. Alpha channels can be used to indicate to Enblend that certain portions of an input image should not contribute to the final image.

Enblend does not align images. Use a tool such as hugin or PanoTools to do this. The TIFF files produced by these programs are exactly what Enblend is designed to work with. Sometimes these GUIs allow you to select feathering for the edges of your images. This treatment is detrimental to Enblend. Turn off feathering by deselecting it or setting the feather width to zero.

Enblend blends the images in the order they are specified on the command line. You should order your images according to the way that they overlap, for example from left-to-right across the panorama. If you are making a multi-row panorama, we recommend blending each horizontal row individually, and then running Enblend a last time to blend all of the rows together vertically.

Enblend reads all layers of multi-layer images, like, for example, multi-directory TIFF images2. The input images are processed in the order they appear on the command line. Multi-layer images are processed from the first layer to the last before Enblend considers the next image on the command line.

Find out more about Enblend on its SourceForge web page.

2 Workflow

Enblend and Enfuse are parts of a chain of tools to assemble images.

Figure:photographic-workflow shows where Enblend and Enfuse sit in this tool chain.


Figure 2.1: Photographic workflow with Enblend and Enfuse.

Take Images
Take multiple images to form a panorama, an exposure series, a focus stack, etc.
          There is one exception with Enfuse when a single raw image is
          converted multiple times to get several – typically differently
          “exposed” – images.

Exemplary Benefits

Remaining Problem: The “overlayed” images may not fit together, that is the overlay regions may not match exactly.

Convert Images
Convert the raw data exploiting the full dynamic range of the camera and capitalize on a high-quality conversion.
Align Images
Align the images so as to make them match as well as possible.
          Again there is one exception and this is when images naturally align.
          For example, a series of images taken from a rock solid tripod with a
          cable release without touching the camera, or images taken with a
          shift lens, can align without further user intervention.

This step submits the images to affine transformations. If necessary, it rectifies the lens' distortions (e.g. barrel or pincushion), too. Sometimes even luminance or color differences between pairs of overlaying images are corrected (“photometric alignment”).

Benefit: The overlay areas of images match as closely as possible given the quality if the input images and the lens model used in the transformation.

Remaining Problem: The images may still not align perfectly, for example, because of parallax errors, or blur produced by camera shake.

Combine Images
Enblend and Enfuse combine the aligned images into one.

Benefit: The overlay areas become imperceptible for all but the most mal-aligned images.

Remaining Problem: Enblend and Enfuse write images with an alpha channel. (For more information on alpha channels see Understanding Masks.) Furthermore, the final image rarely is rectangular.

Postprocess the combined image with your favorite tool. Often the user will want to crop the image and simultaneously throw away the alpha channel.




3 Invocation

enblend [OPTIONS] [--output=IMAGE] INPUT...

Assemble the sequence of images INPUT... into a single IMAGE.

Input images are either specified literally or via so-called response files (see below). The latter are an alternative to specifying image filenames on the command line.

3.1 Response Files

A response file contains names of images or other response filenames. Introduce response file names with an at-character (‘@’).

Enblend and Enfuse process the list INPUT strictly from left to right, expanding response files in depth-first order. (Multi-layer files are processed from first layer to the last.) The following examples only show Enblend, but Enfuse works exactly the same.

Solely image filenames.
          enblend image-1.tif image-2.tif image-3.tif

The ultimate order in which the images are processed is: image-1.tif, image-2.tif, image-3.tif.

Single response file.
          enblend @list

where file list contains


Ultimate order: img1.exr, img2.exr, img3.exr, img4.exr.

Mixed literal names and response files.
          enblend @master.list image-09.png image-10.png

where file master.list comprises of


first.list is


and second.list contains


Ultimate order: image-01.png, image-02.png, image-03.png, image-04.png, image-05.png, image-06.png, image-07.png, image-08.png, image-09.png, image-10.png,

3.1.1 Response File Format

Response files contain one filename per line. Blank lines or lines beginning with a sharp sign (‘#’) are ignored; the latter can serve as comments. Filenames that begin with an at-character (‘@’) denote other response files. Table:response-file-format states a formal grammar of response files in EBNF.

response-file ::= line*
line ::= (comment | file-spec) [‘\r’] ‘\n
comment ::= space* ‘#text
file-spec ::= space* ‘@filename space*
space ::= ‘ ’ | ‘\t

where text is an arbitrary string and filename is any filename.

Table 3.1: EBNF definition of the grammar of response files.

In a response file relative filenames are used relative the response file itself, not relative to the current-working directory of the application.

The above grammar might unpleasantly surprise the user in the some ways.

Whitespace trimmed at both line ends
For convenience, whitespace at the beginning and at the end of each line is ignored. However, this implies that response files cannot represent filenames that start or end with whitespace, as there is no quoting syntax. Filenames with embedded whitespace cause no problems, though.
Only whole-line comments
Comments in response files always occupy a complete line. There are no “line-ending comments”. Thus, in
          # exposure series
          img-0.33ev.tif # "middle" EV

only the first line contains a comment, whereas the second line includes none. Rather, it refers to a file called ‘img-0.33ev.tif # "middle" EV.

Image filenames cannot start with ‘@
An at-sign invariably introduces a response file, even if the filename's extension hints towards an image.

If Enblend or Enfuse do not recognize a response file, they will skip the file and issue a warning. To force a file being recognized as a response file add one of the following syntactic comments to the first line of the file.

     response-file: true
     enblend-response-file: true
     enfuse-response-file: true

Finally, here is an example of a valid response file.

     # 4\pi panorama!
     # These pictures were taken with the panorama head.
     # Freehand sky shot.
     # "Legs, will you go away?" images.

3.1.2 Syntactic Comments

Comments that follow the format described in Table:response-file-syntactic-comment are treated as instructions how to interpret the rest of the response file. A syntactic comment is effective immediately and its effect persists to the end of the response file, unless another syntactic comment undoes it.

syntactic-comment ::= space* ‘#space* key space* ‘:space* value
key ::= (‘A’ .. ‘Z’ | ‘a’ .. ‘z’ | ‘-’)+

where value is an arbitrary string.

Table 3.2: EBNF definition of the grammar of syntactic comments in response files.

Unknown syntactic comments are silently ignored.

3.1.3 Globbing Algorithms

The three equivalent syntactic keys

control the algorithm that Enblend or Enfuse use to glob filenames in response files.

All versions of Enblend and Enfuse support at least two algorithms: literal, which is the default, and wildcard. See Table:globbing-algorithms for a list of all possible globbing algorithms. To find out about the algorithms in your version of Enblend or Enfuse team up the options --version and --verbose.

Do not glob. Interpret all filenames in response files as literals. This is the default.

Please keep in mind that whitespace at both ends of a line in a response file always gets discarded.

Glob using the wildcard characters ‘?’, ‘*’, ‘[’, and ‘]’.

The W*N32 implementation only globs the filename part of a path, whereas all other implementations perform wildcard expansion in all path components. Also see glob(7).

Alias for literal.
The shell globbing algorithm works as literal does. In addition, it interprets the wildcard characters ‘{’, ‘}’, and ‘~’. This makes the expansion process behave more like common UN*X shells.
Alias for shell.

Table 3.3: Globbing algorithms for the use in response files


     # Horizontal panorama
     # 15 images
     # filename-globbing: wildcard

3.2 Common Options

Common options control some overall features of Enblend.

Pre-assemble non-overlapping images before each blending iteration.

This overrides the default behavior which is to blend the images sequentially in the order given on the command line. Enblend will use fewer blending iterations, but it will do more work in each iteration.

Write a compressed output file.

Depending on the output file format Enblend accepts different values for COMPRESSION.

COMPRESSION is a JPEG quality level ranging from 0–100.
COMPRESSION is one of the keywords:
Do not compress. This is the default.
Use the Deflate compression scheme also called ZIP-in-TIFF. Deflate is a lossless data compression algorithm that uses a combination of the LZ77 algorithm and Huffman coding.
Use Lempel-Ziv-Welch (LZW) adaptive compression scheme. LZW compression is lossless.
Use PackBits compression scheme. PackBits is particular variant of run-length compression. It is lossless.

Any other format
Other formats do not accept a COMPRESSION setting.

However, VIGRA automatically compresses png-files with the Deflate method.

Print information on the available options and exit.
Use at most this many LEVELS for pyramid 3 blending if LEVELS is positive, or reduce the maximum number of levels used by −LEVELS if LEVELS is negative.

The number of levels used in a pyramid controls the balance between local and global image features (contrast, saturation, ...) in the blended region. Fewer levels emphasize local features and suppress global ones. The more levels a pyramid has, the more global features will be taken into account.

As a guideline, remember that each new level works on a linear scale twice as large as the previous one. So, the zeroth layer, the original image, obviously defines the image at single-pixel scale, the first level works at two-pixel scale, and generally, the n-th level contains image data at 2^n-pixel scale. This is the reason why an image of width×height pixels cannot be deconstructed into a pyramid of more than

⌊ log 2 ⁡ ( min ⁡ width height ) ⌋ levels.

If too few levels are used, “halos” around regions of strong local feature variation can show up. On the other hand, if too many levels are used, the image might contain too much global features. Usually, the latter is not a problem, but is highly desired. This is the reason, why the default is to use as many levels as is possible given the size of the overlap regions. Enblend may still use a smaller number of levels if the geometry of the overlap region demands.

Positive values of LEVELS limit the maximum number of pyramid levels. Depending on the size and geometry of the overlap regions this may or may not influence any pyramid. Negative values of LEVELS reduce the number of pyramid levels below the maximum no matter what the actual maximum is and thus always influence all pyramids.

The valid range of the absolute value of LEVELS is 1 to 29.

Place output in FILE.

If --output is not specified, the default is to put the resulting image in a.tif.

Without an argument, increase the verbosity of progress reporting. Giving more --verbose options will make Enblend more verbose. Directly set a verbosity level with a non-negative integral LEVEL.

Each level includes all messages of the lower levels.

only warnings and errors
reading and writing of images
mask generation, pyramid, and blending
reading of response files, color conversions
image sizes, bounding boxes and intersection sizes
detailed information on the optimizer runs (Enblend only)
estimations of required memory in selected processing steps

The default verbosity level of Enblend is 1.

Output information on the Enblend version.

Team this option with --verbose to inquire about configuration details, like the extra features that have been compiled in.

Blend around the boundaries of the panorama.

With this option Enblend treats the panorama of width w and height h as an infinite data structure, where each pixel P(x, y) of the input images represents the set of pixels S_P(x, y)4.

MODE takes the following values:

This is a “no-op”; it has the same effect as not giving --wrap at all. The set of input images is considered open at its boundaries.
Wrap around horizontally: S P x y = { P x + m ⁢ w y : m   in   Z } . This is useful for 360° horizontal panoramas as it eliminates the left and right borders.
Wrap around vertically: S P x y = { P x y + n ⁢ h : n   in   Z } . This is useful for 360° vertical panoramas as it eliminates the top and bottom borders.
Wrap around both horizontally and vertically: S P x y = { P x + m ⁢ w y + n ⁢ h : m , n   in   Z } . In this mode, both left and right borders, as well as top and bottom borders, are eliminated.

Specifying --wrap without MODE selects horizontal wrapping.

Checkpoint partial results to the output file after each blending step.

3.3 Extended Options

Extended options control the image cache, the color model, and the cropping of the output image.

Set the BLOCKSIZE in kilobytes (KB) of Enblend's image cache.

This is the amount of data that Enblend will move to and from the disk at one time. The default is 2048KB, which should be ok for most systems. See Tuning Memory Usage for details.

Note that Enblend must have been compiled with the image-cache feature for this option to be effective. Find out about extra features with enblend --version --verbose.

Use the CIECAM02 color appearance model for blending colors.

The input files should have embedded ICC profiles if this option is specified. If no ICC profile is present, Enblend will assume that the image uses the sRGB color space. The difference between this option and Enblend's default color blending algorithm is very slight and will only be noticeable when areas of different primary colors are blended together.

Force the number of bits per channel and the numeric format of the output image.

Enblend always uses a smart way to change the channel depth to assure highest image quality (at the expense of memory), whether requantization is implicit because of the output format or explicit with option --depth.

All DEPTH specifications are valid in lowercase as well as uppercase letters. For integer format, use

8, uint8
Unsigned 8bit; range: 0..255
Signed 16bit; range: −32768..32767
16, uint16
Unsigned 16bit; range: 0..65535
Signed 32bit; range: −2147483648..2147483647
32, uint32
Unsigned 32bit; range: 0..4294967295

For floating-point format, use

r32, real32, float
IEEE754 single precision floating-point, 32bit wide, 24bit significant
  • Minimum normalized value: 1.2 × 10 -38
  • Epsilon: 1.2 × 10 -7
  • Maximum finite value: 3.4 × 10 38

r64, real64, double
IEEE754 double precision floating-point, 64bit wide, 53bit significant
  • Minimum normalized value: 2.2 × 10 -308
  • Epsilon: 2.2 × 10 -16
  • Maximum finite value: 1.8 × 10 308

If the requested DEPTH is not supported by the output file format, Enblend warns and chooses the DEPTH that matches best.

The OpenEXR data format is treated as IEEE754 float internally. Externally, on disk, OpenEXR data is represented by “half” precision floating-point numbers.

OpenEXR half precision floating-point, 16bit wide, 10bit significant

Set the size of the output image manually to WIDTH×HEIGHT. Optionally specify the X-OFFSET and Y-OFFSET, too.

This option is useful when the input images are cropped TIFF files, such as those produced by nona. The stitcher nona is part of Hugin. See Helpful Programs.

Save alpha channel as “associated”. See the TIFF documentation for an explanation.

Gimp (before version 2.0) and Cinepaint (see Helpful Programs) exhibit unusual behavior when loading images with unassociated alpha channels. Use option -g to work around this problem. With this flag Enblend creates the output image with the associated alpha tag set, even though the image is really unassociated alpha.

Use the graphics card – in fact the graphics processing unit (GPU) – to accelerate some computations.

This is an experimental feature that may not work on all systems. In this version of Enblend, 4.0-753b534c819d, only mask optimization strategy 1 benefits from this option.

Note that GPU-support must have been compiled into Enblend for this option to be available. Find out about this feature with enblend --version --verbose.

Set the CACHESIZE in megabytes (MB) of Enblend's image cache.

This is the amount of memory Enblend will use for storing image data before swapping to disk. The default is 1024MB which is good for systems with 3–4gigabytes (GB) of RAM. See Tuning Memory Usage for details.

Note that Enblend must have been compiled with the image-cache feature for this option to be effective. Find out about extra features with enblend --version --verbose.

3.4 Mask Generation Options

These options control the generation and the usage of masks.

Set the parameters of the Simulated Annealing optimizer used in Optimizer Strategy 1 (see Table:optimizer-strategies).
TAU is the temperature reduction factor in the Simulated Annealing; it also can be thought of as “cooling factor”. The closer TAU is to one, the more accurate the annealing run will be, and the longer it will take.

Append a percent sign (‘%’) to specify TAU as a percentage.

Valid range:

0 < TAU < 1 .

The default is 0.75; values around 0.95 are reasonable. Usually, slower cooling results in more converged points.

DELTA-E-MAX and DELTA-E-MIN are the maximum and minimum cost change possible by any single annealing move.

Valid range:


In particular they determine the initial and final annealing temperatures according to:

T initial = DELTA-E-MAX log &ApplyFunction; ( K-MAX / ( K-MAX - 2 ) ) T final = DELTA-E-MIN log &ApplyFunction; ( K-MAX 2 - K-MAX - 1 )

The defaults are: DELTA-E-MAX: 7000.0 and DELTA-E-MIN: 5.0.

K-MAX is the maximum number of “moves” the optimizer will make for each line segment. Higher values more accurately sample the state space, at the expense of a higher computation cost.

Valid range:

K-MAX 3.

The default is 32. Values around 100 seem reasonable.

Use a scaled-down version of the input images to create the seam line. This option reduces the number of computations necessary to compute the seam line and the amount of memory necessary to do so. It is the default.

If omitted FACTOR defaults to 8, this means, option --coarse-mask shrinks the overlapping areas by a factor of 8 ×

8. With FACTOR = 8 the total memory allocated during a run of Enblend shrinks approximately by 80% and the maximum amount of memory in use at a time is decreased to 60% (Enblend compiled with image cache) or 40% (Enblend compiled without image cache).

Valid range: FACTOR = 1, 2, 3,....

Also see Table:mask-generation.

--no-optimize --optimize

--fine-mask Use NFT mask. Vectorize NFT mask, optimize vertices with simulated annealing and Dijkstra's shortest path algorithm, fill vector contours.

--coarse-mask Scale down overlap region, compute NFT mask and vectorize it, fill vector contours. Scale down overlap region, vectorize NFT mask, optimize vertices with simulated annealing and Dijkstra's shortest path algorithm, fill vector contours.

Table 3.4: Various options that control the generation of masks. All mask computations are based on the Nearest-Feature Transformation (NFT) of the overlap region.

Set the search RADIUS of the Dijkstra Shortest Path algorithm used in Optimizer Strategy 2 (see Table:optimizer-strategies).

A small value prefers straight line segments and thus shorter seam lines. Larger values instruct the optimizer to let the seam line take more detours when searching for the best seam line.

Valid range:


Default: 25pixels.

Instruct Enblend to employ the full-size images to create the seam line, which can be slow. Use this option, for example, if you have very narrow overlap regions.

Also see Table 3.4.

Instead of generating masks, use those in IMAGE-TEMPLATE. The default is mask-%n.tif.

See --save-masks below for details.

Set the mask vectorization DISTANCE Enblend uses to partition each seam. Thus, break down the seam to segments of length DISTANCE each.

If Enblend uses a coarse mask (--coarse-mask) or Enblend optimizes (--optimize) a mask it vectorizes the initial seam line before performing further operations. See Table 3.4 for the precise conditions. DISTANCE tells Enblend how long to make each of the line segments called vectors here.

The unit of DISTANCE is pixels unless it is a percentage as explained in the next paragraph. In fine masks one mask pixel corresponds to one pixel in the input image, whereas in coarse masks one pixel represents for example 8pixels in the input image.

Append a percentage sign (‘%’) to DISTANCE to specify the segment length as a fraction of the diagonal of the rectangle including the overlap region. Relative measures do not depend on coarse or fine masks, they are recomputed for each mask. Values around 5%–10% are a good starting point.

This option massively influences the mask generation process! Large DISTANCE values lead to shorter, straighter, less wiggly, less baroque seams that are on the other hand less optimal, because they run through regions of larger image mismatch instead of avoiding them. Small DISTANCE values give the optimizers more possibilities to run the seam around high mismatch areas.

What should never happen though, are loops in the seam line. Counter loops with higher weights of DISTANCE-WEIGHT (in option --optimizer-weights), larger vectorization DISTANCEs, TAUs (in option --anneal) that are closer to one, and blurring of the difference image with option --smooth-difference. Use option --visualize to check the results.

Valid range:

DISTANCE 4 . Enblend limits DISTANCE so that it never gets below 4 even if it has been given as a percentage. The user will be warned in such cases.

Default: 4pixels for coarse masks and 20pixels for fine masks.

Turn off seam line optimization. Combined with option --fine-mask this will produce the same type of mask as Enblend version 2.5, namely the result of a Nearest-Feature Transform (NFT).5

Also see Table 3.4.

Use a two-strategy approach to route the seam line around mismatches in the overlap region. This is the default. Table:optimizer-strategies explains these strategies; also see Table 3.4.
Stragegy 1: Simulated Annealing
Tune with option --anneal = TAU : DELTA-E-MAX : DELTA-E-MIN : K-MAX.


Stragegy 2: Dijkstra Shortest Path
Tune with option --dijkstra = RADIUS.

Dijkstra algorithm

Table 3.5: Enblend's two strategies to optimize the seam lines between images.

Set the weights of the seam-line optimizer. If omitted, MISMATCH-WEIGHT defaults to 1.

The seam-line optimizer considers two qualities of the seam line:

The optimizer weights DISTANCE-WEIGHT and MISMATCH-WEIGHT define how to weight these two criteria. Enblend up to version 3.2 used 1:1. This version of Enblend (4.0-753b534c819d) uses 8.0:1.0.

A large DISTANCE-WEIGHT pulls the optimized seam line closer to the initial postion. A large MISMATCH-WEIGHT makes the seam line go on detours to find a path along which the mismatch between the images is small. If the optimized seam line shows cusps or loops (see option --visualize), reduce MISMATCH-WEIGHT or increase DISTANCE-WEIGHT.

Both weights must be non-negative. They cannot be both zero at the same time. Otherwise, their absolute values are not important as Enblend normalizes their sum.

Save the generated masks to IMAGE-TEMPLATE. The default is mask-%n.tif. Enblend saves masks as 8bit grayscale (single channel) images. For accuracy we recommend to choose a lossless format.

Use this option if you wish to edit the location of the seam line by hand. This will give you images of the right sizes that you can edit to make your changes. Later, use --load-masks to blend the project with your custom seam lines.

IMAGE-TEMPLATE defines a template that is expanded for each input file. In a template a percent sign (‘%’) introduces a variable part. All other characters are copied literally. Lowercase letters refer to the name of the respective input file, whereas uppercase ones refer to the name of the output file (see Common Options). Table:mask-template-characters lists all variables.

A fancy mask filename template could look like this:


It puts the mask files into the same directory as the output file (‘%D’), generates a two-digit index (‘%02n’) to keep the mask files nicely sorted, and decorates the mask filename with the name of the associated input file (‘%f’) for easy recognition.

Smooth the difference image prior to seam-line optimization to get a shorter and – on the length scale of RADIUS – also a straighter seam-line. The default is not to smooth.

If RADIUS is larger than zero Enblend blurs the difference images of the overlap regions with a Gaussian filter having a radius of RADIUSpixels. Values of 0.5 to 1.5pixels for RADIUS are good starting points; use option --visualize to directly judge the effect.

When using this option in conjunction with  --coarse-mask=FACTOR, keep in mind that the smoothing occurs after the overlap regions have been shrunken. Thus, blurring affects a FACTOR×FACTOR times larger area in the original images.

Valid range:

0.0 RADIUS .
Create an image according to VISUALIZE-TEMPLATE that visualizes the mask optimization process. The default is vis-%n.tif.

The image shows Enblend's view of the overlap region and how it decided to route the seam line. If you are experiencing artifacts or unexpected output, it may be useful to include this visualization image in your bug report. See Bug Reports.

VISUALIZE-TEMPLATE defines a template that is expanded for each input file. In a template, a percent sign (‘%’) introduces a variable part; all other characters are copied literally. Lowercase letters refer to the name of the respective input file, whereas uppercase ones refer to the name of the output file (see Common Options). Table:mask-template-characters lists all variables.

Visualization Image The visualization image shows the symmetric difference of the pixels in the rectangular region where two images overlap. The larger the difference the lighter shade of gray it appears in the visualization image. Enblend paints the non-overlapping parts of the image pair – these are the regions where no blending occurs – in dark red. Table:visualization-colors shows the meanings of all the colors that are used in seam-line visualization images.

dark red
Non-overlapping parts of image pair.
various shades of gray
Difference of the pixel values in the overlap region.
dark blue
Location of an optimizer sample.
medium green
First sample of a line segment.
light green
Any other but first sample of a line segment.
bright cyan
State space sample inside the Dijkstra radius.
bright magenta
Non-converged point.
dark yellow
Initial seam line as generated by the NFT.

Enblend marks a non-movable (“frozen”) endpoint of a seam-line segment with a bright white cross, whereas it uses a light orange diamond to denote an endpoint that the optimizer may move around.

bright yellow
Final seam line.

Table 3.6: Colors used in seam-line visualization images.

Produces a literal ‘%’-sign.
Expands to the index of the mask file starting at zero.

%i’ supports setting a pad character or a width specification:

          % PAD WIDTH i

PAD is either ‘0’ or any punctuation character; the default pad character is ‘0’. WIDTH is an integer specifying the minimum width of the number. The default is the smallest width given the number of input images, this is 1 for 2–9 images, 2 for 10–99 images, 3 for 100–999 images, and so on.

Examples: ‘%i’, ‘%02i’, or ‘%_4i’.

Expands to the number of the mask file starting at one. Otherwise it behaves identically to ‘%i’, including pad character and width specification.
This is the full name (path, filename, and extension) of the input file associated with the mask.

Example: If the input file is called /home/luser/snap/img.jpg, ‘%p’ expands to /home/luser/snap/img.jpg, or shorter: ‘%p’ ⇒ /home/luser/snap/img.jpg.

This is the full name of the output file.
Is replaced with the directory part of the associated input file. see dirname.

Example (cont.): ‘%d’ ⇒ /home/luser/snap.

Is replaced with the directory part of the output file.
Is replaced with the non-directory part (often called “basename”) of the associated input file. see basename.

Example (cont.): ‘%b’ ⇒ img.jpg.

Is replaced with the non-directory part of the output file.
Is replaced with the filename without path and extension of the associated input file.

Example (cont.): ‘%f’ ⇒ img.

Is replaced with the filename without path and extension of the output file.
Is replaced with the extension (including the leading dot) of the associated input file.

Example (cont.): ‘%e’ ⇒ .jpg.

Is replaced with the extension of the output file.

Table 3.7: Special characters to control the generation of mask filenames.

4 Understanding Masks

A binary mask indicates for every pixel of an image if this pixel must be considered in further processing, or ignored. For a weight mask, the value of the mask determines how much the pixel contributes, zero again meaning “no contribution”.

Masks arise in two places: as part of the input files and as separate files, showing the actual pixel weights prior to image blendung or fusion. We shall explore both occurrences in the next sections.

4.1 Masks in Input Files

Each of the input files for Enfuse and Enblend can contain its own mask. Both applications interpret them as binary masks no matter how many bits per image pixel they contain.

Use ImageMagick's identify or, for TIFF files, tiffinfo to inquire quickly whether a file contains a mask. Helpful Programs shows where to find these programs on the web.

     $ identify -format "%f %m %wx%h %r %q-bit" remapped-0000.tif
     remapped-0000.tif TIFF 800x533 DirectClassRGBMatte 8-bit
                                                  ^^^^^ mask
     $ tiffinfo remapped-0000.tif
     TIFF Directory at offset 0x1a398a (1718666)
       Subfile Type: (0 = 0x0)
       Image Width: 800 Image Length: 533
       Resolution: 150, 150 pixels/inch
       Position: 0, 0
       Bits/Sample: 8
       Sample Format: unsigned integer
       Compression Scheme: PackBits
       Photometric Interpretation: RGB color
       Extra Samples: 1<unassoc-alpha>            <<<<< mask
       Orientation: row 0 top, col 0 lhs
       Samples/Pixel: 4                           <<<<< R, G, B, and mask
       Rows/Strip: 327
       Planar Configuration: single image plane

The “Matte” part of the image class and the “Extra Samples” line tell us that the file features a mask. Also, many interactive image manipulation programs show the mask as a separate channel, sometimes called “Alpha”. There, the white (high mask value) parts of the mask enable pixels and black (low mask value) parts suppress them.

The multitude of terms all describing the concept of a mask is confusing.

A mask defines a selection of pixels. A value of zero represents an unselected pixel. The maximum value (“white”) represents a selected pixel and the values between zero and the maximum are partially selected pixels. See Gimp-Savy.
Alpha Channel
The alpha channel stores the transpacency value for each pixel, typically in the range from zero to one. A value of zero means the pixel is completely transparent, thus does not contribute to the image. A value of one on the other hand means the pixel is completely opaque.
The notion “matte” as used by ImageMagick refers to an inverted alpha channel, more precisely: 1 - alpha. See ImageMagick for further explanations.

Enblend and Enfuse only consider pixels that have an associated mask value other than zero. If an input image does not have an alpha channel, Enblend warns and assumes a mask of all non-zero values, that is, it will use every pixel of the input image for fusion.

Stitchers like nona add a mask to their output images.

Sometimes it is helpful to manually modify a mask before fusion. For example to suppress unwanted objects (insects and cars come into mind) that moved across the scene during the exposures. If the masks of all input images are black at a certain position, the output image will have a hole in that position.

4.2 Weight Mask Files


5 Tuning Memory Usage

The default configuration of Enblend and Enfuse assumes a system with 3–4GB of RAM.

If Enblend and Enfuse have been compiled with the “image-cache” feature, they do not rely on the operating system's memory management, but use their own image cache in the file system. To find out whether your version uses the image cache say

     enblend --verbose --version


     enfuse --verbose --version

Enblend and Enfuse put the file that holds the image cache either in the directory pointed to by the environment variable TMPDIR, or, if the variable is not set, in directory /tmp. It is prudent to ensure write permissions and enough of free space on the volume with the cache file.

The size of the image cache is user configurable with the option ‘-m CACHE-SIZE’ (see Extended Options). Furthermore, option ‘-b BUFFER-SIZE’ (see Extended Options) allows for fine-tuning the size of a single buffer inside the image cache. Note that CACHE-SIZE is given in megabytes, whereas the unit of BUFFER-SIZE is kilobytes.

Usually the user lets the operating system take care of the memory management of all processes. However, users of Enblend or Enfuse might want to control the balance between the operating systems' Virtual Memory system and the image cache for several reasons.

The CACHE-SIZE should be set in such a way as to reconcile all of the above aspects even for the biggest data sets, that is, projects with many large images.

Table:cache-size-settings suggests some cache- and buffer-sizes for different amounts of available RAM.

4096 1024 2048 default
2048 512–1024 1024
1024 256–512 256–512

Table 5.1: Suggested cache-size settings

On systems with considerably more than 4GB of RAM it is recommended to run Enblend or Enfuse versions without image cache.

6 Helpful Additional Programs

Several programs and libraries have proven helpful when working with Enfuse and Enblend.

Raw Image Conversion

Image Alignment and Rendering

Image Manipulation

High Dynamic Range


Meta-Data Handling

Appendix A Bug Reports

     Most of this appendix was taken from the
     Octave documentation.

Bug reports play an important role in making Enblend and Enfuse reliable and enjoyable.

When you encounter a problem, the first thing to do is to see if it is already known. On the package's SourceForge homepage click “Develop” and on the development page click “Tracker”. Search the trackers for your particular problem. If it is not known, then you should report the problem.

In order for a bug report to serve its purpose, you must include the information that makes it possible to fix the bug.

A.1 Have You Really Found a Bug?

If you are not sure whether you have found a bug, here are some guidelines:

A.2 How to Report Bugs

The fundamental principle of reporting bugs usefully is this: report all the facts. If you are not sure whether to state a fact or leave it out, state it. Often people omit facts because they think they know what causes the problem and they conclude that some details do not matter. Play it safe and give a specific, complete example.

Keep in mind that the purpose of a bug report is to enable someone to fix the bug if it is not known. Always write your bug reports on the assumption that the bug is not known.

Try to make your bug report self-contained. If we have to ask you for more information, it is best if you include all the previous information in your response, as well as the information that was missing.

To enable someone to investigate the bug, you should include all these things:

A.3 Sending Patches for Enblend or Enfuse

If you would like to write bug fixes or improvements for Enblend or Enfuse, that is very helpful. When you send your changes, please follow these guidelines to avoid causing extra work for us in studying the patches. If you do not follow these guidelines, your information might still be useful, but using it will take extra work.

Appendix B Authors

Andrew Mihal ( has written Enblend and Enfuse.


Thanks to Simon Andriot and Pablo Joubert for suggesting the Mertens-Kautz-Van Reeth technique and the name “Enfuse”.

Appendix C GNU Free Documentation License

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Program Index

Syntactic-Comment Index

Option Index

General Index


[1] Peter J. Burt and Edward H. Adelson, “A Multiresolution Spline With Application to Image Mosaics”, ACM Transactions on Graphics, Vol. 2, No. 4, October 1983, pages 217–236.

[2] Use utilities like, e.g., tiffcopy and tiffsplit of LibTIFF to manipulate multi-directory TIFF images. See Helpful Programs.

[3] As Dr. Daniel Jackson correctly noted, actually, it is not a pyramid: “Ziggaurat, it's a Ziggaurat.”

[4] Solid-state physicists will be reminded of the, Born-von Kármán boundary condition.

[5] Muhammad H. Alsuwaiyel and Marina Gavrilova, “On the Distance Transform of Binary Images”, Proceedings of the International Conference on Imaging Science, Systems, and Technology, June 2000, Vols. I and II, pages 83–86.

[6] Images of a size less than 1500×1000 pixels qualify as small.