From: Petter Reinholdtsen Date: Sun, 1 May 2005 11:35:15 +0000 (+0000) Subject: Start on assignemnt report. X-Git-Url: http://pere.pagekite.me/gitweb/homepage.git/commitdiff_plain/bf0399f2e02a849df79bc7fbac24302e42a5f14b?hp=65c967c79adcfbea0547c5057d6ec5b95184e0c6 Start on assignemnt report. --- diff --git a/mypapers/drafts/geg2210/assignment-8.html b/mypapers/drafts/geg2210/assignment-8.html new file mode 100644 index 0000000000..65838c4969 --- /dev/null +++ b/mypapers/drafts/geg2210/assignment-8.html @@ -0,0 +1,224 @@ + + + + + + + +

+ +Here are my notes from today. + + +Logged into jern.uio.no using ssh to run ERDAS Imagine. Started by +using 'imagine' on the command line. The images were loaded from +/mn/geofag/gggruppe-data/geomatikk/ + +Tried to use svalbard/tm87.img, but it only have 5 bands. Next tried +jotunheimen/tm.img, which had 7 bands. + +The pixel values in a given band is only a using a given range of +values. This is because sensor data in a single image rarely extend +over the entire range of possible values. + +Evaluation of the different bands +================================= + +band 1, blue (0.45-0.52 um) +--------------------------- + + Visible light, and will display a broad range of values both over + land and water. Reflected from ice, as those are visible white and + reflect all visible light waves. Histogram show most values between + 30 and 136. Mean values of 66.0668. There are one wide peak with + center around 50. There are two peaks at 0 and 255. + +band 2, green (0.52-0.60 um) +---------------------------- + + Visible light, and will display a broad range of values both over + land and water. Reflected from ice, as those are visible white and + reflect all visible light waves. Histogram show most values from 8 + to 120. The mean value is 30.9774. There are two main peaks at 20 + and 27. There is also a pie at 0. + +band 3, red (0.60-0.69 um) +-------------------------- + + Visible light, and will display a broad range of values both over + land and water. Reflected from ice, as those are visible white and + reflect all visible light waves. Histogram show most values from 33 + t 135, with one wide peak around 52. There are also seem to be two + peaks at 0 and 255. The mean value is 34.3403. + +band 4, near-infraread (0.76-0.90 um) +------------------------------------- + + Water acts as an absorbing body so in the near infrared spectrum, + water features will appear dark or black meaning that all near + infrared bands are absorbed. On the other hand, land features + including ice, act as reflector bodies in this band. The histogram + show most values between 7 and 110. The mean is 40.1144. There are + two peaks at 7 and 40. + +band 5, mid-infrared (1.55-1.75 um) +----------------------------------- + + The ice, glaciers and water do not reflect any mid-infrared light. + The histogram show most values between 1 and 178. The mean is + 49.8098 and there are two peaks at 6 and 78, in addition to two + peaks at 0 and 255. + +band 6, thermal infrared (10.4-12.5 um) +--------------------------------------- + + Display the temperature on earth. We can for example see that the + ice is colder than the surrounding areas. The histogram show most + values between 36 to 122. The mean is 102.734. There are one wide + peak around 53, in addition to two peaks at 0 and 255. + +band 7, mid-infrared (2.08-2.35 um) +------------------------------------ + + The ice, glaciers and water do not reflect any mid-infrared + frequencies. The histogram show most values between 77 and 150. + The mean is 24.04, and there are one wide peak at 130 and a smaller + peak at 83, in addition to one peak at 0. + +Image enhancement +----------------- + +We can get a good contrast stretch by using the histogram +equalisation. This will give us the widest range of visible +separation between features. + +Displaying colour images +------------------------ + +Comparing a map we found on the web, + +and the standard infrared image composition, we can identify some +features from the colors used: + + - water is black or green + + - ice and glaciers are white, while snow is light green. + + - vegetation is red. + + - non-vegetation is brown or dull red when closer to snow and + glaciers. + +Next, we tried to shift the frequencies displayed to use blue for the +red band, green for the near ir band and red for the mid ir (1.55-1.75 +um). With this composition, we get some changes in the colours of +different features: + + - water is black + + - ice and glaciers are light blue, while snow is dark blue. + + - vegetation is light green and yellow. + + - non-vegetation is red or brown. + +Filtering and image sharpening +============================== + +We decided to work on the grey scale version of the thermal infrared. +This one has lower resolution then the rest of the bands, with 120m +spatial resolution while the others have 30m spatial resolution. + +The high pass filtering seem to enhance the borders between the +pixels. Edge detection gave us the positions of glaciers and water. +We tried a gradient filter using this 3x3 matrix: [ 1 2 -1 / 2 0 -2 / +1 -2 -1 ]. It gave a similar result to the edge detection. + + +We also tried unsharp filtering using this 3x3 matrix: [ -1 -1 -1 / -1 +8 -1 / -1 -1 -1 ]. This gave similar results to the edge detection +too. + +We started to suspect that the reason the 3x3 filters gave almost the +same result was that the fact that the spatial resolution of the +thermal band is actually 4x4 pixels. Because of this, we tried with a +5x5 matrix, making sure it sums up to 0. + + -1 -1 -1 -1 -1 + -1 -1 -1 -1 -1 + -1 -1 24 -1 -1 + -1 -1 -1 -1 -1 + -1 -1 -1 -1 -1 + +Next, we tried some different weight: + + -1 -1 -1 -1 -1 + -1 -2 -2 -2 -1 + -1 -2 32 -2 -1 + -1 -2 -2 -2 -1 + -1 -1 -1 -1 -1 + +This one gave more lines showing the borders between the thermal +pixels. + +From: shanette Dallyn +Subject: Re: My notes from todays exercise +To: Petter Reinholdtsen +Date: Sat, 30 Apr 2005 15:16:59 -0400 (EDT) + +Hey Petter! + Allright, I looked up some stuff on statistics and the most valuable +conclusion that I can come up with for the histograpm peak question is: +"The peak values of the histograms represent the the spectral sensitivity +values that occure the most often with in the image band being analysed" + +For the grey level question go to http://www.cs.uu.nl/wais/html/na-dir/sci/ +Satellite-Imagery-FAQ/part3.html I found this and thought that the first major +paragraph pretty much answered the question for the grey levels. + +theory of convolution: + + Specialty Definition: Convolution + + (From Wikipedia, the free Encyclopedia) + +In mathematics and in particular, functional analysis, the convolution +(German: Faltung) is a mathematical operator which takes two functions and and +produces a third function that in a sense represents the amount of overlap +between and a reversed and translated version of . + +The convolution of and is written . It is defined as the integral of the +product of the two functions after one is reversed and shifted. + +The integration range depends on the domain on which the functions are +defined. In case of a finite integration range, and are often considered as +cyclically extended so that the term does not imply a range violation. Of +course, extension with zeros is also possible. + +If and are two independent random variables with probability densities and , +respectively, then the probability density of the sum is given by the +convolution . + +For discrete functions, one can use a discrete version of the convolution. It +is then given by + +When multiplying two polynomials, the coefficients of the product are given by +the convolution of the original coefficient sequences, in this sense (using +extension with zeros as mentioned above). + +Generalizing the above cases, the convolution can be defined for any two +square-integrable functions defined on a locally compact topological group. A +different generalization is the convolution of distributions. + +I hope this will help! + +Shanette + +

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