OTB.FineRegistration: Estimate disparity map between two images.

This application computes a disparity map between two images that correspond to the same scene. It is intended for case where small misregistration between images should be estimated and fixed. The search is performed in 2D.The algorithm uses an iterative approach to estimate a best match between local patches. The typical use case is registration betwween similar bands, or between two acquisitions. The output image contains X and Y offsets, as well as the metric value. A sub-pixel accuracy can be expected. The input images should have the same size and same physical space.

Inputs

The reference image.

format
href
Please set a value for ref.

The secondary image.

format
href
Please set a value for sec.

The output image contains 3 bands, for X offset, Y offset and the metric value. It may contain a 4th one with the validity mask (if used).

string
Please set a value for out.

The exploration radius along x (in pixels)

integer
Please set a value for erx.

The exploration radius along y (in pixels)

integer
Please set a value for ery.

Radius along x (in pixels) of the metric computation window

integer
Please set a value for mrx.

Radius along y (in pixels) of the metric computation window

integer
Please set a value for mry.

The image to warp after disparity estimation is completed.

format
href
Please set a value for w.

The output warped image

string

Coarse offset along x (in physical space) between the two images, used as an initial offset for all pixels.

number

Coarse offset along y (in physical space) between the two images, used as an initial offset for all pixels.

number

Generates a result at a coarser resolution with a given sub-sampling rate along X

number

Generates a result at a coarser resolution with a given sub-sampling rate along Y

number

Performs a gaussian smoothing of the reference image. Parameter is gaussian sigma (in pixels) in X direction.

number

Performs a gaussian smoothing of the reference image. Parameter is gaussian sigma (in pixels) in Y direction.

number

Performs a gaussian smoothing of the secondary image. Parameter is gaussian sigma (in pixels) in X direction.

number

Performs a gaussian smoothing of the secondary image. Parameter is gaussian sigma (in pixels) in Y direction.

number

Choose the metric used for block matching. Available metrics are cross-correlation (CC), cross-correlation with subtracted mean (CCSM), mean-square difference (MSD), mean reciprocal square difference (MRSD) and mutual information (MI). Default is cross-correlation

string

Metric extrema location will be refined up to the given accuracy. Default is 0.01

number

Metric extrema will be refined up to the given accuracy. Default is 0.01

number

Lower threshold to compute the validity mask. This mask will be the 4th output band.

number

Upper threshold to obtain a validity mask. This mask will be the 4th output band.

number

Available memory for processing (in MB)

integer

Outputs

The output image contains 3 bands, for X offset, Y offset and the metric value. It may contain a 4th one with the validity mask (if used).

format
transmission

The output warped image

format
transmission

Execution options

successUri
inProgressUri
failedUri

format

mode

Execute End Point

View the execution endpoint of a process.

View the alternative version in HTML.

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Parameter is gaussian sigma (in pixels) in Y direction.", "description": "Performs a gaussian smoothing of the secondary image. Parameter is gaussian sigma (in pixels) in Y direction.", "schema": {"type": "number", "nullable": true}, "id": "sgsy"}, "m": {"title": "Choose the metric used for block matching. Available metrics are cross-correlation (CC), cross-correlation with subtracted mean (CCSM), mean-square difference (MSD), mean reciprocal square difference (MRSD) and mutual information (MI). Default is cross-correlation", "description": "Choose the metric used for block matching. Available metrics are cross-correlation (CC), cross-correlation with subtracted mean (CCSM), mean-square difference (MSD), mean reciprocal square difference (MRSD) and mutual information (MI). Default is cross-correlation", "schema": {"type": "string", "nullable": true}, "id": "m"}, "spa": {"title": "Metric extrema location will be refined up to the given accuracy. 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This mask will be the 4th output band.", "schema": {"type": "number", "nullable": true}, "id": "vmut"}, "ram": {"title": "Available memory for processing (in MB)", "description": "Available memory for processing (in MB)", "schema": {"type": "integer", "default": 128, "nullable": true}, "id": "ram"}}, "outputs": {"out": {"title": "The output image contains 3 bands, for X offset, Y offset and the metric value. It may contain a 4th one with the validity mask (if used).", "description": "The output image contains 3 bands, for X offset, Y offset and the metric value. 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http://tb17.geolabs.fr:8119/ogc-api/processes/OTB.FineRegistration.html
Last modified: Sat Feb 19 15:43:34 CET 2022