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Master's Piece

Reports, reports, reports. Sunday, October 11, 2009. Activity 19: Restoration of Blurred Image. In this activity, we restore a motion blurred image with Gaussian noise using a Weiner filter and a pseudo Weiner filter. In the Fourier space, the degraded image is given by. Where G is the degraded image, F is the original image, N is the noise, H is the transfer function given by. Where T is the duration of exposure, a and b represents displacements along u and v respectively. Where K is a constant. Figure ...

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Master's Piece | thejaggernaut.blogspot.com Reviews

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Reports, reports, reports. Sunday, October 11, 2009. Activity 19: Restoration of Blurred Image. In this activity, we restore a motion blurred image with Gaussian noise using a Weiner filter and a pseudo Weiner filter. In the Fourier space, the degraded image is given by. Where G is the degraded image, F is the original image, N is the noise, H is the transfer function given by. Where T is the duration of exposure, a and b represents displacements along u and v respectively. Where K is a constant. Figure ...

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Master's Piece | thejaggernaut.blogspot.com Reviews

https://thejaggernaut.blogspot.com

Reports, reports, reports. Sunday, October 11, 2009. Activity 19: Restoration of Blurred Image. In this activity, we restore a motion blurred image with Gaussian noise using a Weiner filter and a pseudo Weiner filter. In the Fourier space, the degraded image is given by. Where G is the degraded image, F is the original image, N is the noise, H is the transfer function given by. Where T is the duration of exposure, a and b represents displacements along u and v respectively. Where K is a constant. Figure ...

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thejaggernaut.blogspot.com

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Master's Piece: September 2009

http://www.thejaggernaut.blogspot.com/2009_09_01_archive.html

Reports, reports, reports. Saturday, September 19, 2009. Activity 17: Photometric Stereo. Photometric stereo uses light intensity from different light sources to infer the shape of a three-dimensional surface. For this activity we used four images of a sphere illuminated with four light sources positioned at different locations. For each source, the corresponding images are the following. Figure 1. Images. The reconstruction is shown below. Figure 2. Reconstruction. Activity 16: Neural Network. For this ...

2

Master's Piece: October 2009

http://www.thejaggernaut.blogspot.com/2009_10_01_archive.html

Reports, reports, reports. Sunday, October 11, 2009. Activity 19: Restoration of Blurred Image. In this activity, we restore a motion blurred image with Gaussian noise using a Weiner filter and a pseudo Weiner filter. In the Fourier space, the degraded image is given by. Where G is the degraded image, F is the original image, N is the noise, H is the transfer function given by. Where T is the duration of exposure, a and b represents displacements along u and v respectively. Where K is a constant. Figure ...

3

Master's Piece: June 2009

http://www.thejaggernaut.blogspot.com/2009_06_01_archive.html

Reports, reports, reports. Wednesday, June 24, 2009. Activity 2: Area Estimation for Images with Defined Edges. To compute for the area of arbitrary binary images, we will make use of Green's theorem. The test images are as follow. Figure 1. Rectangle with dimension190x115. Figure 2. Ellipse which can be enclosed in a rectangle of dimension 200x100. Figure 3. Irregular shape. Figure 4. Image containing two contours. The results are as follows. Table 1. Summary of results. I=im2bw(I,0.5);. Below are the d...

4

Master's Piece: Activity 19: Restoration of Blurred Image

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

Reports, reports, reports. Sunday, October 11, 2009. Activity 19: Restoration of Blurred Image. In this activity, we restore a motion blurred image with Gaussian noise using a Weiner filter and a pseudo Weiner filter. In the Fourier space, the degraded image is given by. Where G is the degraded image, F is the original image, N is the noise, H is the transfer function given by. Where T is the duration of exposure, a and b represents displacements along u and v respectively. Where K is a constant. Figure ...

5

Master's Piece: July 2009

http://www.thejaggernaut.blogspot.com/2009_07_01_archive.html

Reports, reports, reports. Sunday, July 26, 2009. Activity 7: Enhancement in the Frequency Domain. Fourier transform of an image gives the spatial frequencies present in it. Because of this property of the FT it has been used to remove unwanted patterns. It will be demonstrated later how this fact will help improve the quality of an image. Convolution simply means "a little bit of the other". The FT of a convolution of two functions in space is the product of the two functions' FT. FT [ f ∗g ]=FG. Figure...

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jrvitug.blogspot.com

Chocolate lover: July 2011

http://jrvitug.blogspot.com/2011_07_01_archive.html

Wednesday, July 13, 2011. Even if everybody thinks you're not. I still believe that you are". We are human beings. not perfect. but we shouldn't be deprived of the chance to improve ourselves and show the society the better side of us. Just some random thoughts from a very lazy evening. I remember the time when I last spoke about this. Subscribe to: Posts (Atom).

jrvitug.blogspot.com

Chocolate lover: Happy weekend ^_^

http://jrvitug.blogspot.com/2011/06/happy-weekend.html

Friday, June 17, 2011. And so my day ended very happily! I know God will not let things happen without lessons to be learned. I will always trust in You Lord. What a happy weekend indeed! Subscribe to: Post Comments (Atom). I was just so scared.

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: ACTIVITY 17 - Stereometry

http://malese-ous.blogspot.com/2009/09/activity-17-stereometry.html

Monday, September 14, 2009. ACTIVITY 17 - Stereometry. The easiest case to work with would be a point source of light. The intensity would depend as 1/r 2, where r is the distance from the point source. The mathematical derivations will not be. Shown here. Just note that we need information on the different positions of the light source relative to the object and the following images. After applying some matrix operations, we obtain the following reconstruction. Figure 2. Reconstruction.

malese-ous.blogspot.com

Malese-ous: June 2009

http://malese-ous.blogspot.com/2009_06_01_archive.html

Monday, June 29, 2009. Activity 4 - Enhancement by Histogram Manipulation. Contrast is an important characteristic of images. It enables us to distinguish details. However, conditions may not be optimized to meet the desired contrast. It is often necessary to digitally process images to enhance its appearance. I rate this entry 10 for completing the activity and successfully backprojecting, which was the tricky part in my opinion. Xbasc();/ to clear image window. Old=trial(i);/ enhanced image. New=(old-d...

otarun.blogspot.com

Pixel of Knowledge: lessons from drinking sessions part 2..

http://otarun.blogspot.com/2010/10/lessons-from-drinking-sessions-part-2.html

On pics, physics, and more! Thursday, October 7, 2010. Lessons from drinking sessions part 2. Second round of drinking session, this time with my good friend wert, we talked to our friends dad and he shared with us several key points. Below are the things that I remember :). Key thing that I remember is "never be complacent, strive for greatness and avoid the trap of mediocrity. Other things he also mentioned are the following:. 2 marijuana is good. smells good - hehe. :). 5 make mistakes while young.

malese-ous.blogspot.com

Malese-ous: ACTIVITY 16 - Neural Networks

http://malese-ous.blogspot.com/2009/09/activity-16-neural-networks-unfinished.html

Wednesday, September 2, 2009. ACTIVITY 16 - Neural Networks. We present here yet another method of classifying objects. We will not consider the details but present the overall procedure when using neural networks. Figure 1. Schematic of a neural network. Figure 2. Values as a function of number of iterations. Figure 3. Plot of the values as a function of iterations for one object. For this system, the classification works best at about 4000-5000 iterations. In other words, the compromise between spe...

malese-ous.blogspot.com

Malese-ous: Activity 15 - Probabilistic Classification

http://malese-ous.blogspot.com/2009/08/activity-15-probabilistic.html

Wednesday, August 26, 2009. Activity 15 - Probabilistic Classification. Objects can be classified into categories based on features that can be measured. In the previous activity, we determine class membership by determining which mean feature vector it is closer to. However, this may prove tricky when the distributions fall along parallel lines, for instance. A feature vector may fall along the line crossing one mean vector but be nearer the other mean vector. An object with a particular measurement x.

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Master's Piece

Reports, reports, reports. Sunday, October 11, 2009. Activity 19: Restoration of Blurred Image. In this activity, we restore a motion blurred image with Gaussian noise using a Weiner filter and a pseudo Weiner filter. In the Fourier space, the degraded image is given by. Where G is the degraded image, F is the original image, N is the noise, H is the transfer function given by. Where T is the duration of exposure, a and b represents displacements along u and v respectively. Where K is a constant. Figure ...

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