- 45 Views
- Uploaded on
- Presentation posted in: General

NAPP Photo Five Pockets near Dubois

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

NAPP Photo

Five Pockets near Dubois

Google Earth

Geometric Corrections

Rectification and Registration

- 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)

- 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

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

- 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.

Image Coordinate Frame (row/column)

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

- 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 mathematicaltransformation(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?

- 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

- Transformation: Use a mathematical equation to transform all image GCP coordinates to best match the real world GCP coordinates.
- Resampling: Assign new DNs to the pixels once they have been moved to their new positions.

Result of erroneous GCP coordinates or placement.

Mathematical Transformations

Real World Coordinates

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

Image Coordinates

- 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

- 3rd Order
- Requires minimum of 10 GCPs
- Very rugged terrain

- Typically want at least 3x the minimum number of GCPs

Raw Image

(No spatial relationship to location on earth)

Transformed Image

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

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

- 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)!

- 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

- Increase the resolution (artificially make pixels smaller)

- 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!).

- 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.)