Distributed Gradient-Domain Processing of Planar and Spherical Images (Version 1)

links description executable usage

LINKS
ToG 2010 Paper
Windows Executables
Source Code
License

CODE DESCRIPTION

Stitching: Given an input image consisting of composited images, and given a mask which assigns the same color ID to pixels coming from the same source image, our code outputs the stitched image whose gradients are a best-fit to the gradients of the composite image, with forced zero gradients across seam boundaries.
Smoothing/Sharpening: Given an input image, a gradient modulation term, and a pixel fidelity term, our code outputs the best-fit image whose gradients match the modulated gradients of the input image and whose pixel values match the pixel values of the original image. Formally, if F is the original image, α is the fidelity term, and β is the gradient modulation term, the output image G is the image minimizing the sum of square norms:

ServerSocket: This executable acts as the hub of the solver. Clients connect to it, it establishes all necessary connections and orchestrates the solver. It is also responsible for solving the linear system once multigrid has reduced the problem size to a size that can be solved on a single core.
ClientSocket: This executable is the client-side of the solver, and is responsible for managing the solution of a subset of the image. The clients can be distributed across a network and only require that the subset of the image that they are responsible for is on a locally accessible disk. Since these clients can be run in a multi-threaded fashion, there should be no reason to run multiple clients off of the same physical machine.

EXECUTABLE ARGUMENTS

ServerSocket:

--count <client count>
This integer specifies the number of clients that will be connecting to the server.
[--port <server port>]
This optional integer specifies the port at which the server should listen for client requests. If no port is specified, the server will ask the system to provide and one, and will print out the address and port to the command line.
[--iters <number of Gauss-Seidel iterations>]
This optional integer specifies the number of Gauss-Seidel iterations that should be performed per pass. (Default value is 5.)
[--minMGRes <coarsest resolution of the multigrid solver>]
This optional integer specifies the coarsest resolution at which Gauss-Seidel relaxation should be performed by the multigrid solver. Once the solver reaches this resolution, it solves using a conjugate-gradients solver. (Default value is 64.)
[--inCoreRes <in-core/out-of-core transition resolution>]
This optional integer specifies the transition at which the solver should switch from a distributed solver to a serial solver. (Default value is 1024.)
[--verbose]
If this optional argument is specified, the solver will output the magnitude of the residuals at the different levels.
[--progress]
If this optional argument is specified, the solver will show the progress of the solver through the restriction and prolongation phases.
[--noBlackOut]
By default, if the mask value is white (255, 255, 255) the solver interprets this as an unknown color, forces the pixel value to black, and does not zero-out the seam-crossing gradient. Enabling this flag tells the solver that a zero seam-crossing gradient is desired.
[--quality <JPEG compression quality>]
This optional integer, in the range [0,100], specifies the compression quality that should be used if the output image is in JPEG format. (Default value is 100.)
[--hdr]
By default, the output image pixels are represented at 8 bits per pixel. When using either PNG or TIFF output, enabling this flag will output the images at 16 bits per pixel.
[--tileWidth <iGrid tile width>]
[--tileHeight <iGrid tile height>]
[--tileExt <iGrid tile extnsion>]
When outputting to a tiled grid of images in iGrid format, these parameters specify the width, height, and file-type for the output tiles. The default resolution for the output tiles is 8192x8192 and the default file type is JPG.
[--iWeight <pixel fidelity term>]
If the system is solving the Poisson equation to perform image smoothing or sharpening, this value specifies the fidelity term α.
[--gScale <gradient modulation term>]
If the system is solving the Poisson equation to perform image smoothing or sharpening, this value specifies the gradient modulation β.

ClientSocket:

--pixels <input composite image>
This string is the the name of the image file containing the image band that this client is responsible for. (Currently supported file-types include PNG, JPEG, BMP, WDP, TIFF, and our tiled image format iGrid.) The image height is unconstrained (though it must be the same across all clients). However, the width for all but the last band should be a multiple of a nice-power of two. (Roughly, the power should be equal to the number of levels over which the solver is parallelized.)
--labels <input mask image>
This string is the name of the image file serving as the mask for stitching. (Since the values of the mask are used to determine if adjacent pixels in the composite image come from the same source, the mask should not be compressed using lossy compression. Similarly, in representing the composited pixels, be wary of using JPEG compression. Even at 100% quality, it can blur out the seams between images, so that setting the seam-crossing gradient to zero is no longer sufficient.)
This parameter is required when performing stiching, as it lets the system know where to set the seam-crossing gradients to zero. However, when performing smoothing or sharpening (i.e. if a value is specified for either of the server parameters --iWeight and --gScale), then this parameter is ignored and the system assumes that all the pixels come from a single image.
--out <ouput image>
This string is the name of the image to which the output will be written.
--address <server address>
This string specifies the address to which the client should connect in order to establish a connection with the server.
--port <server port>
This integer specifies the port to which the client should connect in order to establish a connection with the server.
[--index <client index>]
This optional integer specifies the index of the band within the whole image that the client is reponsible for. Indexing starts at zero, and if no value is specified, the client is by default assigned an index of zero.
[--temp <scratch directory>]
This optional string specifies the directory to which the temporary I/O streams used for storing data between the restriction and prolongation are to be written out.
[--threads <number of threads>]
This optional integer specifies the number of threads the client should spawn in order to solve its part of the problem. (Default value is 1.)
[--inCore]
By default, the executable assumes that the problem is large and uses a solver that streams the system to and from disk. If this argument is specified, the entire system will be solved in-core.

USAGE
For testing purposes, two sample datasets are provided.

PNC3: This dataset, courtesty of Matt Uyttendaele, consists of a panorama of 7 images resulting in an image of resolution 7,963 x 3,589.
For distributed processing, the image and the mask are broken up into two roughly uniform-sized bands, shown below.

Composite

Mask

Process 0 Bands Process 1 Bands

To obtain the stitched image, we first run the server, letting it know that there will be two processes connecting to it:
ServerSocket.exe --count 2
which gives an output of:
Server Address: 123.456.789.101:11213
Using the address and the port, we can now start up the clients. We start the first client, specifying the input and output data, the address and port for connecting to the server, the number of threads to use for processing, and the index of the band:
ClientSocket.exe --pixels pixels.0.png --labels labels.0.png --out out.0.jpeg --address 123.456.789.101 --port 11213 --threads 2 --index 0 --inCore
Similarly, we start the second client:
ClientSocket.exe --pixels pixels.1.png --labels labels.1.png --out out.1.jpeg --address 123.456.789.101 --port 11213 --threads 1 --index 1 --inCore
The resulting, stitched, image bands are:

Process 0 Output Process 1 Output

Alternatively, if we just want to run on a single machine, we set up the server to expect a single connection, and use the iGrid format to merge the data:
ServerSocket.exe --count 1 --port 12345 ClientSocket.exe --pixels pixels.iGrid --labels labels.iGrid --out out.jpeg --address 127.0.0.1 --port 12345 --threads 3 --inCore
The resulting, stitched, image is:

Process 0 Output
Edinburgh: This dataset, courtesty of Brian Curless, consists of a panorama of 25 images resulting in an image of resolution 16,950 x 2,956 For distributed processing, the image and the mask are broken up into 9 blocks of width 2048, shown below.

Composite

Mask

Process 0 Data Process 1 Data

These images are grouped into two iGrid files for distributed processing over two processors, and we stitch the images by first running the server, letting it know that there will be two processes connecting to it:
ServerSocket.exe --count 2 --port 11213 --tileWidth 5000 --tileHeight 5000 --tileExt jpg
Then, we run the two clients:
ClientSocket.exe --address 123.456.789.101:11213 --index 0 --pixels pixels.0.iGrid --labels labels.0.iGrid --out out.0.iGrid ClientSocket.exe --address 123.456.789.101:11213 --index 1 --pixels pixels.1.iGrid --labels labels.1.iGrid --out out.1.iGrid
The resulting, stitched, image bands are:

Process 0 Output Process 1 Output

Using the stitched output, we can now perform gradient-domain sharpening and smoothing by specifying gradient modulation and pixel fidelity terms. To smooth the images, we specify that we would like to set the gradients to zero while preserving the pixel values:
ServerSocket.exe --count 2 --port 11213 --iWeight 0.005 --gScale 0 --tileWidth 5000 --tileHeight 5000 --tileExt jpg ClientSocket.exe --address 123.456.789.101:11213 --index 0 --pixels out.0.iGrid --out smooth.0.iGrid ClientSocket.exe --address 123.456.789.101:11213 --index 1 --pixels out.1.iGrid --out smooth.1.iGrid
and to sharpen the data we amplify the gradients while preserving the pixel values:
ServerSocket.exe --count 2 --port 11213 --iWeight 0.005 --gScale 2 --tileWidth 5000 --tileHeight 5000 --tileExt jpg ClientSocket.exe --address 123.456.789.101:11213 --index 0 --pixels out.0.iGrid --out sharp.0.iGrid ClientSocket.exe --address 123.456.789.101:11213 --index 1 --pixels out.1.iGrid --out sharp.1.iGrid
The smoothed and sharpened image bands are:

Process 0 Output Process 1 Output

Note that the fidelity weight, --iWeight 0.005, was chosen so that the smoothing/sharpening would be perceptible in the down-sampled images displayed on this web-page. In practice the interpolation weight should be set higher, as its value is (roughly) the reciprocal of the width of the smoothing/sharpening filter, in pixels.


Process 0 Output	Process 1 Output


Process 0 Output

HOME

	Process 0 Bands	Process 1 Bands
Composite
Mask

	Process 0 Data				Process 1 Data
Composite
Mask