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Miguel AP 186 blog. Monday, October 5, 2009. Activity 19 Restoration of blurred image. Whatever the degradation process maybe, it can always be modeled as a convolution of the image and the degradation function such that in inverse space we obtained a blurred image given by. Where Sn and Sf are the power spectra of the noise and the ideal (undegraded) image. However, in real life situations it is highly improbable for us to have information on both the additive noise and the ideal (undegraded) image&...

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Miguel AP 186 blog. Monday, October 5, 2009. Activity 19 Restoration of blurred image. Whatever the degradation process maybe, it can always be modeled as a convolution of the image and the degradation function such that in inverse space we obtained a blurred image given by. Where Sn and Sf are the power spectra of the noise and the ideal (undegraded) image. However, in real life situations it is highly improbable for us to have information on both the additive noise and the ideal (undegraded) image&...

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miguel AP 186 blog | ap186-msison.blogspot.com Reviews

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Miguel AP 186 blog. Monday, October 5, 2009. Activity 19 Restoration of blurred image. Whatever the degradation process maybe, it can always be modeled as a convolution of the image and the degradation function such that in inverse space we obtained a blurred image given by. Where Sn and Sf are the power spectra of the noise and the ideal (undegraded) image. However, in real life situations it is highly improbable for us to have information on both the additive noise and the ideal (undegraded) image&...

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ap186-msison.blogspot.com

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miguel AP 186 blog: July 2009

http://www.ap186-msison.blogspot.com/2009_07_01_archive.html

Miguel AP 186 blog. Monday, July 20, 2009. Activity 7 Enhancement in the Frequency Domain. Figure 1. 1st column: Two single pixel dots and its FT. 2nd-5th column: Two circles of varying radius with FT. Figure 2. 1st column: Two single pixel dots and its FT. 2nd-5th column: Two squares of varying side length with FT. Figure 3. 1st column: Two single pixel dots and its FT. 2nd-5th column:. Two gaussians of varying spread (standard deviation/sigma) with FT. Figure 5. Real part of the Fourier transform o...

2

miguel AP 186 blog: June 2009

http://www.ap186-msison.blogspot.com/2009_06_01_archive.html

Miguel AP 186 blog. Sunday, June 28, 2009. Activity 2 Area Estimation for Images with Defined Edges. Green's theorem has been and is still used in various area estimation algorithms. There is even an old area estimating instrument called the planimeter ( http:/ en.wikipedia.org/wiki/Planimeter. Based from this concept I wrote a program in Scilab making use of the SIP toolbox to access the image and the required information from it. In this basic implementation we make use of the function follow(). The ad...

3

miguel AP 186 blog: September 2009

http://www.ap186-msison.blogspot.com/2009_09_01_archive.html

Miguel AP 186 blog. Wednesday, September 9, 2009. Activity 17 Photometric Stereo. Many of our previous activities involved using an objects reflectance, its interaction with a light source, to do color segmentation, white balancing, and even classification. In this activity we will again use the this phenomenon to reconstruct a 3D surface. The method we will be implementing is called photometric stereo. Figure 1. Visualization of Reflection on a 3D surface. Figure 2. Images of the surface taken with ...

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miguel AP 186 blog: Activity 19 Restoration of blurred image

http://www.ap186-msison.blogspot.com/2009/10/activity-19-restoration-of-blurred.html

Miguel AP 186 blog. Monday, October 5, 2009. Activity 19 Restoration of blurred image. Whatever the degradation process maybe, it can always be modeled as a convolution of the image and the degradation function such that in inverse space we obtained a blurred image given by. Where Sn and Sf are the power spectra of the noise and the ideal (undegraded) image. However, in real life situations it is highly improbable for us to have information on both the additive noise and the ideal (undegraded) image&...

5

miguel AP 186 blog: October 2009

http://www.ap186-msison.blogspot.com/2009_10_01_archive.html

Miguel AP 186 blog. Monday, October 5, 2009. Activity 19 Restoration of blurred image. Whatever the degradation process maybe, it can always be modeled as a convolution of the image and the degradation function such that in inverse space we obtained a blurred image given by. Where Sn and Sf are the power spectra of the noise and the ideal (undegraded) image. However, in real life situations it is highly improbable for us to have information on both the additive noise and the ideal (undegraded) image&...

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ccesporlas-ap186.blogspot.com

CINDY 186: Activity 18 | Noise Models and Basic Image Restoration

http://ccesporlas-ap186.blogspot.com/2009/10/activity-18-noise-models-and-basic.html

Monday, October 5, 2009. Activity 18 Noise Models and Basic Image Restoration. Image restoration is a basic image processing application where an image that has been degraded or damaged is being recovered. To recover the image, the degradation must be known and thus can be used in restoring the image. Figure 1. PDFs of different noise types. Figure 2. Types of filtering used. Figure 3. Test image and its PDF. Figure 4 shows the noisy image for the added Gaussian noise with mean = 0.5 and standard dev...

ccesporlas-ap186.blogspot.com

CINDY 186: Activity 17 | Photometric Stereo

http://ccesporlas-ap186.blogspot.com/2009/09/activity-17-photometric-stereo.html

Wednesday, September 9, 2009. Activity 17 Photometric Stereo. Figure 1. Photometric Stereo. Equation 1. Intensity at point P(x,y). In this activity, we use four images of an object taken with different light source positions and use it to reconstruct the 3D structure of the illuminated area, as shown by Figure 2. Figure 2. Images of object at different light source positions. To calculate for the surface normal of the object we need to get the far away point source locations given by V. Buno, Luis III.

otarun.blogspot.com

Pixel of Knowledge: lessons from drinking sessions..part 1.

http://otarun.blogspot.com/2010/10/lessons-from-drinking-sessionspart-1.html

On pics, physics, and more! Sunday, October 3, 2010. Lessons from drinking sessions.part 1. Nakausap ko si Fidel Rillo habang ako ay nakipag-inuman sa bahay ng aming kaibigan (tawagin natin Mambo) bilang despidida nya papuntang Germany. Nais kong ibahagi ang mga bagay na napagusapan namin. Tinanong ako ng "What is God? Isang sagot ang binigay sa akin ng tatay ng aking kaibigan. "it is the search for truth". It is the search for truth.science and God. Subscribe to: Post Comments (Atom).

malese-ous.blogspot.com

Malese-ous: July 2012

http://malese-ous.blogspot.com/2012_07_01_archive.html

Wednesday, July 25, 2012. So I've been away for a really long time.This was an academic blog turned personal blog turned I dunno. As of today, I've decided to use this blog for posting game dev related topics because, hey, I'm a game developer now! Who would have thought? Definitely not the past me. Anyway, I hope I get to keep my promise this time. This only serves as an intro, so nothing game dev related here yet. So there! Subscribe to: Posts (Atom).

adrian-ap186.blogspot.com

Adventures of a Bookworm: June 2009

http://adrian-ap186.blogspot.com/2009_06_01_archive.html

Adventures of a Bookworm. Adrian's Applied Physics 186 Blog. Monday, June 29, 2009. Activity 4. Enhancement by Histogram Manipulation. This activity focused on the enhancement of a low resolution image using histogram manipulation. The activity was started by selecting and downloading a low contrast image from the internet. The image is shown below. The image was then resized and converted into grayscale using the im2gray. From the images enhanced using linear and nonlinear function, it can be observed t...

thejaggernaut.blogspot.com

Master's Piece: August 2009

http://thejaggernaut.blogspot.com/2009_08_01_archive.html

Reports, reports, reports. Friday, August 7, 2009. Activity 10: Preprocessing Text. In this activity, we are asked to extract information from a scanned document (figure 1) specifically handwriting. This activity is the integration of the techniques learned from the previous activities. The first task at hand is to clean the image by removing the horizontal and vertical lines present. Here we used filtering just like in activity 7. For this part only a portion of the image is used. Scilab crashes in Wind...

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ap186-msison.blogspot.com

miguel AP 186 blog

Miguel AP 186 blog. Monday, October 5, 2009. Activity 19 Restoration of blurred image. Whatever the degradation process maybe, it can always be modeled as a convolution of the image and the degradation function such that in inverse space we obtained a blurred image given by. Where Sn and Sf are the power spectra of the noise and the ideal (undegraded) image. However, in real life situations it is highly improbable for us to have information on both the additive noise and the ideal (undegraded) image&...

ap186-ni-moy.blogspot.com

ap186 blog ni momoy...

Ap186 blog ni momoy. Get h1n1 online ;p . reading entries = getting "the virus" for free :D. Monday, October 12, 2009. Activity 19: Restoration of Blurred Image. In this activity, we will apply Weiner filtering to restore an image of known degradation (in this case, blur) and additive noise. The process we followed for this activity is shown below:. In the Fourier space, this can be written as. To restore the image, we use the Weiner filter given below:. Where K is a specified constant. In this activity,...

ap186.blogspot.com

Applied Physics 186

Friday, October 14, 2011. This last experiment is about image processing using the frames of a video-captured scene. Videos are merely a string of still images captured at a certain frequency. This of course is still ruled by the Nyquist criterion to ensure a non-aliased signal (the video itself) in the perception of our eyes. This frequency is more known as the frame rate. Our selected time frame consisted of 14 still images. Figure 1. Sample of a still frame from our video. Finally, these 14 images wer...

ap186niraffy.blogspot.com

ap186 ni raffy

Wednesday, September 30, 2009. THIS IN THEORY IS THE LAST POST IN THIS BLOG! Activity 19: Restoration of Blurred Images. To demonstrate the concept of motion blur and its restoration as well as basic noise filtering. Scilab with SIP toolbox. We begin with an ordinary image with text written on it, in this case we use a grayscale image of the Apollo 13 Mission Patch with the words "Apollo XIII" and "Ex Luna Scientia.". We are in theory to simulate motion blur using the equation:. As usual Mr. Cabello ...

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