Create a simulated natural color image from a MSS image.
MSSCOLOR extrapolates from all MSS channels to generate a blue band and a simulated natural color image. Landsat MSS contains green and red bands, but does not contain a blue band. Input MSS data must have been previously corrected for atmospheric haze. (See User Note 2.)
- IN
- Input image. The input image must contain four bands but may be windowed, subbanded, and of any data type. This algorithm was developed for haze corrected MSS imagery with satellite channels 4, 5, 6, and 7.
- OUT
- Output image. Name of the output simulated natural color image. The output image will have the same number of lines and samples as the input but will have 3 bands (for red, green, blue) instead of 4.
- ODTYPE(SAME)
- Output data type. The data type of the output image.
= SAME: Same as input = BYTE: Byte = I*2: Integer*2 = I*4: Integer*4 = R*4: Real*4
A simulated natural color image named NICEONE will be generated from the atmospherically corrected image, CORRECTED.
Landsat MSS includes channels with sensitivities in the green, red, and infrared portions of the wavelength spectrum. Channel 4 (0.5 to 0.6 micron) is green sensitive, channel 5 (0.6 to 0.7 micron) is red sensitive, and channels 6 and 7 (0.7 to 0.8 and 0.8 to 1.1) are infrared sensitive. Airborne sensors such as MSS often do not contain a blue channel because atmospheric haze often contaminates blue data. MSSCOLOR extrapolates from all MSS bands to create a blue band as part of a natural color image.
Using a ratio of MSS channels 5 and 6, the input pixel is classified as all vegetation, a mixture of vegetation and soil, all soil, or water. Based on this classification, various formulas are selected to compute the output image. The functions used to create the output image have a discontinuity where the ratio of channels 5 and 6 equals 1.5. At this discontinuity, a small change in input values (1 brightness value) can give large changes in output values (20 brightness values).
The algorithm includes the following calculations:
1. For each pixel, the ratio of channels 5 and 6 is first calculated: if (chan6 == 0.0) ratio = chan5 else ratio = chan5 / chan6 2. If (ratio < 0.56), the pixel is classified as vegetation and the output values are calculated as follows: red = 0.75 * chan5 green = 1.50 * chan4 blue = 1.125 * chan4 - 0.1875 * chan6 3. If (0.56 <= ratio < 0.65), the output data is a weighted mixture of the vegetation and soil calculations which appear in steps 2 and 4: weight = (ratio - 0.56) / (0.65 - 0.56) red = weight * chan5 + (1.0 - weight) * 0.75 * chan5 green = weight * 2.0 * chan4 + (1.0 - weight) * chan4 blue = weight * 1.5 * chan4 - 0.25 * chan6 + (1.0 - weight) * 2.0 * chan4 - 0.35 * chan5 - chan7 red = red * 0.75 green = green * 0.75 blue = blue * 0.75 4. If (0.65 <= ratio < 1.50), the pixel is classified as soil: red = 0.5625 * chan5 green = 0.75 * chan4 blue = 0.75 * (2.0 * chan4 - 0.35 * chan5 - chan7) 5. If (1.50 <= ratio), the pixel is classified as water: red = 0.75 * chan5 green = 0.75 * chan4 blue = 0.75 * (2.0 * chan4 - chan5)
A fatal error was encountered. The message displayed preceding this message was the error encountered. Processing terminates.
An error occurred attempting to dynamically allocate memory. Rerun, and if the error persists, contact the system administrator.
The input image is required to have four bands as would correspond to MSS channels 4, 5, 6, and 7 in that order.
The image components specified for IN must all have the same number of lines and samples.
map in="mss(:1)" out=chan4 from=(0 20 255) to=(0 0 235)