Remote Sensing Operations
[Image Processing]

Collaboration diagram for Remote Sensing Operations:


void imProcessNormDiffRatio (const imImage *image1, const imImage *image2, imImage *dst_image)
void imProcessAbnormalHyperionCorrection (const imImage *src_image, imImage *dst_image, int threshold_consecutive, int threshold_percent, imImage *image_abnormal)

Detailed Description

Operations used in Remote Sensing.
See im_process_pnt.h

Function Documentation

void imProcessNormDiffRatio ( const imImage image1,
const imImage image2,
imImage dst_image 

Calculates the Normalized Difference Ratio.
Uses the formula NormDiffRatio = (a-b)/(a+b),
The result image has [-1,1] interval.
Images must be IM_GRAY, and the target image must be IM_FLOAT, except if source is IM_DOUBLE.

im.ProcessNormDiffRatio(image1: imImage, image2: imImage, dst_image: imImage) [in Lua 5] 
im.ProcessNormDiffRatioNew(image1: imImage, image2: imImage) -> new_image: imImage [in Lua 5] 
void imProcessAbnormalHyperionCorrection ( const imImage src_image,
imImage dst_image,
int  threshold_consecutive,
int  threshold_percent,
imImage image_abnormal 

Applies the abnormal pixel correction as described in the article. (Since 3.8)
Images must be IM_GRAY. Source and Target must have the same datatype, and complex is not supported.
image_abnormal is optional, can be NULL. If not NULL, must be IM_BINARY and it will store the abnormal pixels distribution.
Can be done in-place.
threshold_percent is the percentage of the height that must have abnormal pixels candidates.
threshold_consecutive is the minimum number of consecutive abnormal pixels candidates to be considered an abnormal range. (usually the longest vertical ground feature in pixels)

Based on "Detection and Correction of Abnormal Pixels in Hyperion Images" from T. Han, D. G. Goodenough, A. Dyk, and J. Love
im.AbnormalHyperionCorrection(src_image: imImage, dst_image: imImage, threshold_consecutive, threshold_percent: number[, image_abnormal: imImage]) [in Lua 5] 
im.AbnormalHyperionCorrectionNew(src_image: imImage, threshold_consecutive, threshold_percent: number[, image_abnormal: imImage]) -> new_image: imImage [in Lua 5]