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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?
What is the primary cause of distortion in remote sensing images formed from energy detected at high altitudes?
Relief displacement has no effect on remote sensing data products in high-relief terrain.
Relief displacement has no effect on remote sensing data products in high-relief terrain.
False
What is relief displacement?
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.
Serious errors in location due to atmospheric ___ can occur in images formed at acute angles.
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Match the following sources of geometric distortions with their respective descriptions:
Match the following sources of geometric distortions with their respective descriptions:
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Which of the following factors does NOT affect radiance measured by the sensor?
Which of the following factors does NOT affect radiance measured by the sensor?
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Atmospheric correction aims to enhance the visibility of atmospheric particles in imagery.
Atmospheric correction aims to enhance the visibility of atmospheric particles in imagery.
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What is the purpose of the sun elevation correction in radiometric correction?
What is the purpose of the sun elevation correction in radiometric correction?
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The mean distance between the earth and the sun is known as _____ astronomical units.
The mean distance between the earth and the sun is known as _____ astronomical units.
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What effect does the earth-sun distance have on solar irradiance?
What effect does the earth-sun distance have on solar irradiance?
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Match the type of correction with its purpose:
Match the type of correction with its purpose:
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Name one common atmospheric effect that can contaminate satellite imagery.
Name one common atmospheric effect that can contaminate satellite imagery.
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Instrument response characteristics relate to how a sensor records radiance.
Instrument response characteristics relate to how a sensor records radiance.
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What is the purpose of atmospheric correction?
What is the purpose of atmospheric correction?
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Noise in image data can improve the accuracy of radiometric information.
Noise in image data can improve the accuracy of radiometric information.
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What is the process called that converts DNs to absolute radiance?
What is the process called that converts DNs to absolute radiance?
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The appearance of _____ in Landsat MSS data is an example of image noise.
The appearance of _____ in Landsat MSS data is an example of image noise.
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Match the following noise types with their characteristics:
Match the following noise types with their characteristics:
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What can be a consequence of noise in image data?
What can be a consequence of noise in image data?
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Random noise is sometimes referred to as 'salt and pepper' noise.
Random noise is sometimes referred to as 'salt and pepper' noise.
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Name one technique used for noise removal in images.
Name one technique used for noise removal in images.
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Potential sources of noise include _____ or malfunction of a detector.
Potential sources of noise include _____ or malfunction of a detector.
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Which of the following is a common effect of atmospheric conditions on remote sensing images?
Which of the following is a common effect of atmospheric conditions on remote sensing images?
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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
- Example sources of geometric distortions:
- 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.
