napp photo five pockets near dubois. google earth

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NAPP Photo Five Pockets near Dubois

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NAPP Photo

Five Pockets near Dubois

Google Earth

Geometric CorrectionsRectification and Registration

What is Geometric Correction?

Any process that changes the spatial characteristics of pixels. Pixel coordinates (e.g., map projection) Pixel relationship with other pixels Pixel size

Geometric correction also can change the digital numbers of pixels (resampling)

Why Geometric Correction?

To allow an image to overlay a map To eliminate distortion caused by

terrain, instrument wobble, earth curvature, etc.

To change the spatial resolution of an image

To change the map projection used to display an image

Two basic techniques for fitting images to maps

1. Use Ground Control Points (GCPs) to assign real-world coordinates to an image (rectification).

2. Create links between two images or between the image and a digital map to align them with one another (registration)Both techniques are based on same

concept.

Rectification Using GCPs

Object: To match pixel locations in the image to their corresponding locations on the earth

Method: Assign real-world coordinates to known

locations in the image (GCPs) Create a mathematical model to fit the

real-world coordinates to the image coordinates

“Warp” the image to fit the model.

Real World Coordinate Frame (e.g., UTM)

Image Coordinate Frame (row/column)

Ground Control Points (GCPs)

Road intersections, river bends, distinct natural features, etc.

GCPs should be spread across image Requires some minimum number of

GCPs depending on the type of mathematical transformation (model) you use More usually better than fewer!

Some say that it is better to have clusters of GCPs spread across image

Google Earth – Seminoe Reservoir (Wyoming). Where would you locate GCPs?

How is image registration different?

Instead of finding GCPs from a map, you link the same place on two or more images Can be used to georeference an

unreferenced image using a referenced image

Can be used to allow two images to perfectly line up with one another (e.g. images from the same place taken on different dates) even if they aren’t georeferenced

Two main steps necessary to fit an image to a map

1. Transformation: Use a mathematical equation to transform all image GCP coordinates to best match the real world GCP coordinates.

2. Resampling: Assign new DNs to the pixels once they have been moved to their new positions.

Result of erroneous GCP coordinates or placement.

Image Coordinates

Real W

orld

Coord

inate

s

Mathematical Transformations

Points = GCPs; Line = best linear (1st order) fit

Mathematical Transformations

1st Order Requires minimum of 3 GCPs Use for small, flat areas

2nd Order Requires minimum of 6 GCPs Use for larger area where earth curvature is a

factor Use where there is moderate terrain Use with aircraft data where roll, pitch, yaw are

present

Mathematical Transformations (cont.)

3rd Order Requires minimum of 10 GCPs Very rugged terrain

Typically want at least 3x the minimum number of GCPs

Image Transformation (warping)

Raw Image

(No spatial relationship to location on earth)

Transformed Image

(Matches real-world coordinates; Oriented to north, etc.)

Image Resampling

Once an image is warped, how do you assign DNs to the “new” pixels?

Resampling Techniques

Nearest Neighbor Assigns the value of the nearest pixel to

the new pixel location Bilinear

Assigns the average value of the 4 nearest pixels to the new pixel location

Cubic Convolution Assigns the average value of the 16

nearest pixels to the new pixel location

Nearest Neighbor Resampling

Bilinear Resampling

Cubic Convolution Resampling

To maintain image radiometry (DNs) for spectral analysis ALWAYS USE NEAREST NEIGHBOR RESAMPLING!

If your purpose is to produce an image for presentation, bilinear or cubic convolution might work better (can be more visually pleasing).

Remember that EVERY TIME you resample an image for any reason you are altering the original data (DNs)!

Changing Image Spatial Resolution (A type of

Resampling) Two choices

Increase the resolution (artificially make pixels smaller)

Just assign the DN from the original pixel to the smaller pixels that fall inside it

Decrease the resolution (artificially make pixels larger)

Combine the DNs from the original pixels in some way (e.g. average them) to assign a new DN to the bigger pixel

Changing Map Projections

Map projections are mathematical schemes for depicting part of the spherical earth on a flat map or image

Every time you change from one map projection to another you transform and resample (and change the DNs!).

Geometric Correction -- Summary

Essential for almost all remote sensing projects

Critical for combining imagery and GIS

Essential for obtaining spatially accurate products—requires considerable care

Often done for us “at the factory,” but sometimes not, especially for aerial imagery (air photos, etc.)