SEMINAR TOPIC ON SYSTEMATIC AND NON SYSTEMATIC CORRECTION

Views:
 
Category: Education
     
 

Presentation Description

No description available.

Comments

Presentation Transcript

SEMINAR TOPIC ON SYSTEMATIC AND NON SYSTEMATIC CORRECTIION:

SEMINAR TOPIC ON SYSTEMATIC AND NON SYSTEMATIC CORRECTIION NAME: PRAJAPATI KAUSHIK BRANCH: MECH 5 TH SEM NO: 110863119012

Sources of geometric error (main ones in bold):

Sources of geometric error (main ones in bold) Systematic distortions Scan skew : ground swath is not normal to the polar axis – along with the forward motion of the platform during mirror sweep Mirror-scan Velocity and panoramic distortion: along-scan distortion (pixels at edge are slightly larger). This would be greater for off-nadir sensors. Earth rotation: earth rotates during scanning (offset of rows).... (122 pixels per Landsat scene) b. Non-systematic distortions Topography: requires a DEM, otherwise ~ 6 pixel offset in mountains Correcting with a DEM involves ‘orthorectification’ Altitude and attitude variations in satellite: these are minor

Geometric Correction:

Geometric Correction

Pre-Processing Steps:

Pre-Processing Steps Atmospheric correction – Atmospheric conditions at the time of imaging Radiometric correction – Factors influencing scene illumination, sensor matching for multi-temporal comparisons (including noise removal –e.g., sensor striping) Geometric correction – Putting image pixels “in the right place” on the ground

The Source of Geometric Errors in Imagery:

The Source of Geometric Errors in Imagery Systematic Distortions Scan skew (Earth rotation) Changes in mirror scan velocity (not a problem with arrays of detectors) Panoramic distortion (distortions away from nadir) Moving platforms (e.g., satellites)

Example of a Highly Systematic Distortion:

Example of a Highly Systematic Distortion Earth rotation Image = parallelogram Can be de-skewed

Correction of Geometric Distortions:

Correction of Geometric Distortions Systematic geometric distortion is often removed by the image vendor (e.g., EDC, SPOT, GeoEye , Digital Globe) Random Distortions (common with airborne systems) are not always removed , although with modern GPS and IMU capabilities, this is not the problem it once was Altitude: Change in scale if altitude of the platform is altered Attitude: Roll, pitch, and yaw of platform

Correction of Geometric Distortions:

Correction of Geometric Distortions Rectification : Transforming the image into a standard map projection (i.e., fitting the image to a base map ) Map Image

Image Rectification:

Image Rectification Procedure for image rectification Select GCPs Apply coordinate transformation algorithm ( spatial interpolation ) Apply resampling algorithm ( intensity interpolation ) Nearest Neighbor Bilinear Interpolation Cubic Convolution

Image Rectification:

Image Rectification Spatial Interpolation The process involves converting image-file coordinates (e.g., row, column) into map coodinates Polynomial equations are used to rectify the data leading to the conversion A mathematical relationship has to be established between the grid of the base map and the pixel location of the image The equations are developed by modeling the relationship between the GCPs and the corresponding pixel locations in the image being processed

PowerPoint Presentation:

NON SYSTEMATIC CORRECTION

Preprocessing:

Preprocessing Digital Image Processing of satellite images can be divided into: Pre-processing Enhancement and Transformations Classification and Feature extraction Preprocessing consists of: radiometric correction and geometric correction

Preprocessing:

Preprocessing Radiometric Correction: removal of sensor or atmospheric 'noise', to more accurately represent ground conditions - improve image‘fidelity’: correct data loss remove haze enable mosaicking and comparison Geometric correction: conversion of data to ground coordinates by removal of distortions from sensor geometry enable mapping relative to data layers enable mosaicking and comparison

Radiometric Resolution :

Radiometric Resolution

Radiometric correction: modification of DNs:

Radiometric correction: modification of DNs Errors

Why is rectification needed:

Why is rectification needed Raw remote sensing data contain distortions preventing overlay with map layers, comparison between image scenes, and with no geographic coordinates To provide georeferencing To compare/overlay multiple images To merge with map layers To mosaic images e.g. google maps / google earth *** Much imagery now comes already rectified … YEAH !!

Image distortions:

Image distortions In air photos , errors include: topographic and radial displacement; airplane tip, tilt and swing (roll, pitch and yaw). These are less in satellite data due to altitude and stability. The main source of geometric error in satellite data is satellite path orientation (non-polar)

THANK YOU:

THANK YOU

authorStream Live Help