Remote Sensing

Image Rectification and Restoration

Image Rectification and Restoration ► ► ► Geometric correction Radiometric correction Geometric restoration

1. Geometric Correction ► For raw image rectification ► For multi-date images registration ► For multi-resolution images or data layers registration ► Systematic distortion vs. random distortion

Skew Correction Coordinate transfer Pixel value resampling http://rst.gsfc.nasa.gov/Intro/Part2_15.html

Ground Control Points (GCP) ► Features with known locations on a map (X,Y coordinates). These are the “ground control points” ► The same features can be accurately located on the images as well (column, row numbers) ► The features must be well distributed on the map and the image ► Highway intersections are commonly used ground control points

Finding UTM coordinates on a map

Coordinate Transform ► Coordinate transform equations relate geometrically correct map coordinates to the distorted image coordinates x = a 0 + a 1 X + a 2 Y y = b 0 + b 1 X + b 2 Y x,y: column, row number X,Y: coordinates ► Root Mean Square Error (RMSE) = √( d x) 2 + ( d y) 2 Calculate RMSE for all control points

Resampling ► The purpose is to assign pixel values to the empty pixels in the rectified matrix output ► Superimpose the rectified output matrix to the distorted image ► The digital number (DN) of a pixel in the output matrix is assigned based on the DN of its surrounding pixels in the distorted image

Re-sampling Methods ► Nearest neighbor resampling ► Bilinear interpolation ► Cubic convolution resampling

Nearest Neighbor Resampling ► The DN of a pixel in the output matrix is assigned as the DN of the closest pixel in the distorted image ► Advantages simple computation maintain the original values ► Disadvantage spatial offset up to 1/2 pixel

Bi-linear Interpolation ► Distance-weighted average of DN values of the closest 4 pixels ► Advantage ► output image is smoother than the nearest neighbor method Disadvantage alters the original DN values

Cubic Convolution Resampling ► Uses DN values of the closest 16 pixels, adjusted by distance ► Advantage ► smooth output image Disadvantage alters the original DN values

When to Rectify ► ► Rectify before image classification Rectify after image classification

2. Radiometric Corrections Radiometric responses differ by ► dates ► sensor types ► images ► Causes: - Illumination - Atmospheric conditions - View angle or geometry - Instrument response

Radiometric Corrections ► Sun elevation correction ► Atmospheric correction ► Conversion to absolute radiance

Sun Elevation Correction ► DN ------------------------------- Sin (Sun elevation angle) ► Assuming the terrain is flat

Satellite Spring / Fall

Atmospheric Correction ► Haze compensation The DN value of an object (e.g., a deep clear water body) with 0 reflectance = Lp ► Subtract the DN from the entire band

Absolute Irradiance ► Conversion of DN values to absolute radiance values ► It is necessary when compare different sensors, or relate ground measurements to image data ► L = (L max - L min )/255 * DN + L min

3. Geometric Restoration ► ► ► Stripping Line-drop Bit errors

Striping ► Malfunction of a detector ► Use gray scale adjustment to correct the strips

Line Drop ► using average of the above and below lines to fill the dropped line

► Salt and pepper effect due to random error ► Use 3x3 or 5x5 moving window average to remove the noise Bit Error

► Chapter 7 Readings

Earth-Sun Distance Correction ► E 0 Cos q 0 E = ----------- d 2 ► Irradiance is inversely related to the square of the earth-sun distance ► E - normalized solar irradiance ► E 0 - solar irradiance at the mean Earth-sun distance ► ► q 0 - sun angle from the zenith d - Earth-sun distance

Atmospheric Correction r ET ► L tot = --------- + Lp p r reflection of target E - irradiance on the target T - transmission of atmosphere Lp - scattered path radiation