Lab 4: Miscellaneous Image Functions


Goal:
The goal for this lab was to become familiar with image functions such as image subsetting, image fusion, radiometric enhancement, re-sampling, image mosaicking, and binary change detection.

Methods:

Part 1:

Section 1:

This section declared an area of interest with an inquire box. This is done by inputting an image and using the "inquire box" in the raster tools. Once the inquire box is placed so that the study area in within the box, the tool "subset and chip" can be used to create a subset image. Next, the output file needs to be names and a location needs to be selected. The last thing that needs to be done is to run the tool.

Section 2:

This section created an area of interest with a shapefile. The first thing that needs to be done for this is to upload the image you want as well as the shapefile for the desired boundary. From the shapefile, a AOI layer can be made. This layer can be used in the subset and chip tool. Once the input image is put into the tool with the AOI layer from the shapefile, the tool can be run to get an image of only the desired area.

Part 2:

This part of lab 4 creates a higher resolution image from a lower resolution image to optimize the resolution for analysis. This can be done by using the resolution merge tool found in the raster toolbox. The high resolution image and the multi spectral images are selected and the output file named as well as the methods changed to multiplicative and the resampling technique changed to nearest neighbor. Once these are all done, the tool can be run to make a high resolution real color image.

Part 3:

This section uses image functions to reduce haze in the image. For this, the haze reduction tool is used in the radiometric toolbox. Once the tool is opened, the desired image can be used as an input and name the output image and choose its destination. After all this is done, the tool can be run which will result in an image with less haze than the original.

Part 4:

This section connects an image to Google Earth to help with spatial analysis. The first thing that needs to be done is an image needs to be brought into the workspace. Then use the Google Earth toolbox and select "connect to Google Earth". Next, to match the image to Google Earth the "match GE to View" can be used. This will make Google Earth show the same extent as the input image. Next, the image and Google Earth can be synced by clicking the "sync GE to view". This will result in the image and Google Earth being synced, so what ever happens to one image will happen to the other in terms of zooming and panning.

Part 5:

This section uses image functions to change pixel sizes of an image. This can be done with the resample pixel size tool in the spatial tools in the raster toolbox. Once the tool is opened, the input image can be selected and the output file can be named. Next, the re-sampling method can be selected. Once this is complete, the tool can be run to get a resampled image with different cell sizes.

Part 6:

Section 1:

This section takes separate images and combines them into one bigger image. This is done by finding the images that are to be combined and to make sure that the "multiple images in virtual mosaic" is selected and the background transparent and fit to frame are also selected. Next, the Mosaic express tool can be used in the mosaic tool in the raster toolbox. Once the images are uploaded into this tool and the output is named, the tool can be run to create a simple mosaic of the image.

Section 2:

This section takes the same uploaded images from part 6 section 1, but instead of using mosaic express, mosaic pro is used. In the mosaic pro tool, the desired images can be added, make sure the compute active area is selected. Next, the image order needs to be implemented in the model. Next color correction needs to be selected and the use histogram matching needs to be selected. Using the set button in this dialog box, the overlap areas can be selected to preserve the brightness values. Once all of this is done, the tool can be run to get a seamless mosaic image.

Part 7:

Section 1:

This section creates a difference image. This is done by using the two input operators in the raster toolbox. Once the tool is open, the two input images can be uploaded and the output file can be named as well as the operator set to subtract. Next the tool can be run to get a image of the difference between the pixel values. Next, the metadata needs to be accessed for the newly created image. To find the threshold for changed pixels, the standard deviation needs to be multiplied by 1.5 and then added to the mean. This number is then added and subtracted from the mode to get the upper and lower threshold (fig 1).
fig 1. Histogram of the new image with upper and lower thresholds. 
Section 2:

This section maps the change pixels with spatial modeler. In the toolbox tab under model maker, the model maker can be selected and opened. In the modeler, three raster boxes need to be added, two inputs and one output, and a function. The two input rasters need to be selected and the output raster needs to named. Next, the function needs to be declared. For this the older image is subtracted from the new image and then 127 is added. Running this model will result in a cell difference map without negative numbers. The threshold needs to be found for this histogram also. It uses the same steps as before however instead of multiplying by 1.5, the standard deviation is multiplied by 3. Next, another model is needed. This one will have one input and one output raster with on function between them. The input raster will be the output raster from the previous step. The function needs to be changed to conditional and the formula used is "Either 1 if (input_image > threshold) or 0 otherwise". This will make the change areas cell value as 1 and no change area cells as 0. This can now be added to Arcmap to create a map of the change and no change areas.

Results:

Part 1:

Section 1:

The results for this section is a smaller frame for the interested area. This image can be seen below in figure 2.
figure 2. Image subset of area of interest from inquire box.
This area will be a square so if an irregular study area needs to be defined, this is not the tool you want to use.

Section 2:

The result for this section is a area of study in an irregular shape. This can be seen below in figure 3.
figure 3. Area of interest image from shapefile. 
This results in an area of interest in what ever shape the shapefile used is.

Part 2:

The result for this section is a pan sharpened image. This image can be seen below in figure 4. This image has a higher resolution than the previous true color image due to combining it with the panchromatic image.
figure 4. Pan sharpened image.

Part 3:

The result for this section is an image with reduced haze. This image can be seen below in figure 5. This new image is adjusted to reduce the visible haze in the image creating a clearer image.
figure 5. Haze reduced image. 
Part 4:

This section resulted in an image and Google Earth being synced so that when the image in zoomed or panned, Google Earth will do the same thing. This helps because Google Earth can be used as a selective key to help label feature in the image.

Part 5:

This section resulted in two images that were resampled from the same image. The first image was resampled using the nearest neighbors methods (figure 6) and the second image was resampled using bilinear interpolation (figure 7). The images do not look any different from the original, however they can now be used with higher resolution images.
Figure 6. Resampling using nearest neighbors.
Figure 7. Resampling using bilinear interpolation.
Part 6:

Section 1:

This sections result was a mosaic image created using mosaic express. The images are stitched together but they are not seamless. The edge between the image is clearly viable. This image can be seen  below in figure 8.
Figure 8. Mosaic made from mosaic express.
Section 2: 

This selections result was a mosaic image created using mosaic pro. The two images are stitched together with a mostly seamless transition. This image can be seen below in figure 9. 
Figure 9. Mosaic made from mosaic pro. 

Part 7: 

Section 1:  

This section resulted in a histogram with the upper and lower threshold for pixel values of change. This histogram can be seen above in figure 1. 

Section 2: 

This section resulted in a map that shows the pixels that were outside the threshold and inside the threshold. This map can be seen below in figure 10. The areas of change are in red and the areas of no change are in grey. Most of the change is in the northwest and northeast as well as running down the middle from north to south. 
Figure 10. Change/no change map. 
                         


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