Remote Sensing week 7
Remote Sensing week 7 GEOG 2107
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This 2 page Class Notes was uploaded by Ivana Szwejkowski on Monday October 10, 2016. The Class Notes belongs to GEOG 2107 at George Washington University taught by Engstrom, R in Fall 2015. Since its upload, it has received 2 views. For similar materials see Intro to Remote Sensing in Geography at George Washington University.
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Date Created: 10/10/16
Remote Sensing Week 7 Chapter 8 Color theory: Red, Blue, Theory Color Characteristics: Hue, Saturation, Lightness Additive Process; based on light; TV and computer monitor Subtractive Process: based on pigments and dyes; cyan, magenta, and yellow Filters Most aerial photography is collected with filters on the camera lens Block certain wavelengths of light from reaching film plane & exposing film Subtracts some of the light reflected from the scene Yellow filter: absorbs blue (haze) passes green and red. Image Contrast Enhancement Many materials both natural and man-made, have similar reflectance through the electromagnetic spectrum Sensors; detectors must be able to sense a wide range of values- snow to dark volcanic basalt-without becoming saturated ; For sensors with high radiometric resolution, a decrease in contrast may be required if the image DN range exceeds that of the display Utilize full range of video display capabilities ; imagine 8 bit display- 256 grey scale layer ; contrast enhancement is done for display purposes only. (Does not affect actual pixel or DN values) Selection of a contrast enhancement Linear Contrast enhancement Min-Max contrast stretch formula Makes full use of range of output device Quant is the range of brightness values that can be displayed (255) Works best with data that have Gaussian (normal) distribution Min-Max stretch expands the image DN range to fill the dynamic range of the display advance (o-255) Percentage Linear stretch Uses specified Min and Max values that lie in a certain % of pixels from the mean of the histogram A standard deviation from the histogram mean is often used- Standard Deviation stretch. Non-Linear Contrast Enhancement Histogram equalization- assigns an approximately equal number of pixels to each of user-specified gray-scale classes Greatest contrast is applied to most populated range of DN’s. Nonlinear Contrast Enhancement Gaussian- Transforms histogram to bell shaped distribution Log stretch- maximize contrast in dark part of the histogram Inverse Log stretch – maximize contrast in brightest part of the histogram. Multi-Spectral Systems- Chapter 7 Satellite Systems-Overview Sensor system Remote Sensing Raster (Matrix) Data format Terminology - One array of numbers per band - Pixel (abbreviation of “picture element”, smallest 2-D unit of an image, value (brightness value (BV), Digital number (DN), location (x,y)) - Quantization ( conversion of electrical signal to digital number) - Radiometric resolution of signal ( typically in range of 8-12 bits) ASPRS Guide to Land Imaging Systems Civil Land imaging satellites – resolution >= 59 meters - Optical large number in orbit, over 50 countries - Optical large number in orbit, over 50 countries; two major resolution groups o 20 high resolution systems (.5-1.8 meter) o 24 bid resolution systems (2.0-39 meter) - Radar= 10 in orbit, 18 countries Coverage capabilities - Hi-resolution swaths- 8 to 28 km - Mid-resolution swaths-
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