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Remote Sensing: Enhance, Filter and Extract - Home

Images obtained from satellites are not always clear. In many cases the images are affected by noise in the bands, which result from satellite calibration errors, clouds, atmospheric haze or even...

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Images obtained from satellites are not always clear. In many cases the images are affected by noise in the bands, which result from satellite calibration errors, clouds, atmospheric haze or even...
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4 scale factoring
5 extraction
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Remote Sensing: Enhance, Filter and Extract - Home | remotesensingjks.weebly.com Reviews

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Images obtained from satellites are not always clear. In many cases the images are affected by noise in the bands, which result from satellite calibration errors, clouds, atmospheric haze or even...

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Scale Factoring - Remote Sensing: Enhance, Filter and Extract

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Remote Sensing: Enhance, Filter and Extract. We replace the Fuzzy parameter with the Low pass filtering chosen in the last step (FAV: Average low pass filtering). In order to perform the different scaling factors, we followed these steps:. Click on image to enlarge). Original Red Band Images. Click on image to enlarge). True-Colour Images with Linear Enhancement. Click on image to enlarge). False-Colour Images with Linear Enhancement. Click on image to enlarge). False-Colour Images with No Enhancements.

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Original Images - Remote Sensing: Enhance, Filter and Extract

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Remote Sensing: Enhance, Filter and Extract. The following are Thematic Mapper Bands 1 to 5. Click on image to enlarge). Just like the first band the third band has a number of white spots all over the image, making it visually difficult to see certain features. This speckle appearance on the image is more displaced compared to band 1. Like the first two bands, there is a sun stripe artifact at the bottom-left hand corner and a lot of reflectance at the top edge of the large water body.

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Image Filtering - Remote Sensing: Enhance, Filter and Extract

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Remote Sensing: Enhance, Filter and Extract. The next step in our project was to extract the roads from the images. In order to do this we needed to extract the roads from the resulting noise-reduced images and use TM Band 3 (Red Band) in the process after performing a low pass filter and different scaling factors. Scale factoring equation: [RED [(RED – FUZZY). x], x = 2, 8 or 16). Click on image to enlarge). FAV: Averaging (Mean) Low Pass Filter. FME: Median Low Pass Filter. FMO: Mode Low Pass Filter.

4

Final Image (Vector) - Remote Sensing: Enhance, Filter and Extract

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Remote Sensing: Enhance, Filter and Extract. Creating a Vector Layer. After cleaning up the image and having just the roads as the bitmap layer, we can convert this layer into a vector format layer. In order to do that we need to follow these steps:. Click on image to enlarge). Create a free website.

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Extraction - Remote Sensing: Enhance, Filter and Extract

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Remote Sensing: Enhance, Filter and Extract. Extracting an Image Feature: Roads. These steps were followed to perform the Threshold module and create the bitmap layer:. Click on image to enlarge). Noise Removal Techniques: Editing. Create a free website.

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Remote Sensing - Jasdeep K Sagoo

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Comparing Spatial Patterns over the Mount Kenya region, in Northern Kenya from 1987 to 2000 using Remote Sensing Imagery. Remote Sensing: Enhance, Filter and Extract Data. Create a free website. Create your own free website. Start your own free website. A surprisingly easy drag and drop site creator. Learn more.

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