Remote Sensing Lecture 6: Image Rectification

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Questions and Answers

What is the primary cause of distortion in remote sensing images formed from energy detected at high altitudes?

Atmospheric refraction (correct)

Sensor misalignment

Atmospheric scattering

Surface reflection

Relief displacement has no effect on remote sensing data products in high-relief terrain.

False

What is relief displacement?

Relief displacement is the displacement in the position of the image of a ground object due to topographic variation.

Serious errors in location due to atmospheric ___ can occur in images formed at acute angles.

refraction Signup and view all the answers

Match the following sources of geometric distortions with their respective descriptions:

Atmospheric Refraction = Bending of light rays due to atmospheric layers Relief Displacement = Displacement due to topographic variations Sensor Orientation = Misalignment of the sensor during capture Satellite Altitude = Influence of satellite height on image distortion Signup and view all the answers

Which of the following factors does NOT affect radiance measured by the sensor?

Sensor calibration Signup and view all the answers

Atmospheric correction aims to enhance the visibility of atmospheric particles in imagery.

False Signup and view all the answers

What is the purpose of the sun elevation correction in radiometric correction?

To normalize image data acquired under different illumination angles. Signup and view all the answers

The mean distance between the earth and the sun is known as _____ astronomical units.

1 Signup and view all the answers

What effect does the earth-sun distance have on solar irradiance?

It decreases with the square of the distance. Signup and view all the answers

Match the type of correction with its purpose:

Sun elevation correction = Normalizes for the sun's angle Earth-sun distance correction = Accounts for distance changes Atmospheric correction = Retrieves surface reflectance Combined corrections = Adjusts for both sun and distance factors Signup and view all the answers

Name one common atmospheric effect that can contaminate satellite imagery.

Absorption or scattering of radiation. Signup and view all the answers

Instrument response characteristics relate to how a sensor records radiance.

True Signup and view all the answers

What is the purpose of atmospheric correction?

To improve the accuracy of image classification Signup and view all the answers

Noise in image data can improve the accuracy of radiometric information.

False Signup and view all the answers

What is the process called that converts DNs to absolute radiance?

Radiometric correction Signup and view all the answers

The appearance of _____ in Landsat MSS data is an example of image noise.

stripes Signup and view all the answers

Match the following noise types with their characteristics:

Striped Image = Defective lines due to detector variations Line Drop = Spurious DNs along a line due to transmission errors Salt and Pepper Noise = Random noise with a spiky appearance Systematic Noise = Periodic disturbances in the image data Signup and view all the answers

What can be a consequence of noise in image data?

Masked true radiometric information Signup and view all the answers

Random noise is sometimes referred to as 'salt and pepper' noise.

True Signup and view all the answers

Name one technique used for noise removal in images.

Interpolation of DN values Signup and view all the answers

Potential sources of noise include _____ or malfunction of a detector.

periodic drift Signup and view all the answers

Which of the following is a common effect of atmospheric conditions on remote sensing images?

Reduced image clarity Signup and view all the answers

Study Notes

Remote Sensing - Lecture 6: Image Rectification and Restoration

Lecture 6 covers image rectification and restoration concepts in remote sensing.
The lecture outlines image rectification and restoration concepts, geometric correction, radiometric correction, and noise removal.
Students will learn the concepts behind image rectification and restoration.
Students will identify various computer-assisted image rectification and restoration procedures.
Students will learn to conduct computer-assisted procedures through laboratory exercises.
Image rectification and restoration operations aim to correct distorted or degraded image data to create a more faithful representation of the original scene.
Often termed "image pre-processing."
These operations are typically performed before further manipulation and analysis of image data.
Most distortions and degradations result from various factors during image acquisition.
Image rectification and restoration typically involve initial processing raw image data.
Geometric correction ensures that all pixels are correctly geo-referenced, enabling accurate point, line, and area measurements.
- Example sources of geometric distortions:
  - Variations in sensor platform altitude, attitude, and velocity
  - Earth curvature
  - Earth's eastward rotation
  - Atmospheric refraction
  - Relief displacement
Correcting for geometric distortions creates a geographically accurate image.
Radiometric correction converts digital numbers (DNs) to absolute radiance values.
- This is necessary for correcting atmospheric effects and changes in scene illumination.
- Radiometric corrections are useful in situations where changes in scene illumination occur.
Noise removal eliminates noise in the data, for example, stripes, bit errors, etc.
Geometric correction is needed because raw digital images usually contain significant geometric distortions.
These distortions make raw images unusable for direct map use without additional processing.
Methods for geometric corrections:
- Deskewing corrects for distortions caused by Earth's rotation.
Methods for correcting random distortions:
- Analyzing well-distributed ground control points (GCPs) for least squares regression analysis.
The corrected image is then resampled, and various techniques like the nearest neighbor, bilinear interpolation, and bicubic interpolation may be employed.
Resampling methods can also be used for image overlay or registration on multiple dates.
Radiometric correction includes sun elevation and earth-sun distance corrections.
Atmospheric correction aims to remove atmospheric effects causing absorption and scattering in satellite imagery.
Converting DNs to absolute radiance helps quantify ground measurements, like water quality.
Noise removal processes are employed commonly before enhancement/classification.
Some examples and sources of noise are stripes, line drop, and bit errors all of which can alter image quality.

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Description

This quiz focuses on the concepts of image rectification and restoration as discussed in Lecture 6 of Remote Sensing. It covers geometric and radiometric corrections, noise removal, and practical procedures to enhance image quality. Students will engage with computer-assisted techniques to improve distorted or degraded images.