jrvitug.blogspot.com
Chocolate lover: July 2011
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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 ^_^
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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.
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
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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.
jrvitug.blogspot.com
Chocolate lover: Activity 18 Noise model and basic image restoration
http://jrvitug.blogspot.com/2009/10/activity-18-noise-model-and-basic-image.html
Saturday, October 10, 2009. Activity 18 Noise model and basic image restoration. In this activity, we try to demonstrate the different types of noise and image restoration techniques. Similar to image enhancement technique, this method aims to improve the quality of images surrounded with noise. However, this technique is more of object type as compared to image enhancement technique which is subjective in nature. Figure 1. Clean image and its PDF. Where z is the gray level value,. Is the average, and.
malese-ous.blogspot.com
Malese-ous: July 2012
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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).
jrvitug.blogspot.com
Chocolate lover: July 2009
http://jrvitug.blogspot.com/2009_07_01_archive.html
Thursday, July 23, 2009. Enhancement in the Frequency Domain. Image enhancement is any digital process which aims to improve the quality of images by adjusting the contrast, brightness, sharpness, boundaries and edges [1]. One of the techniques used to enhance the visual qualities of images is by filtering out unwanted frequencies. This is done through the use of a mask. A mask is a small square window of values by which the current pixel and its neighbor are weighted to produce and output pixel [1].
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.
gilbert-ap186.blogspot.com
Liknayang Inaplay 186: September 2009
http://gilbert-ap186.blogspot.com/2009_09_01_archive.html
Gilbert's Applied Physics 186 Blog. Thursday, September 24, 2009. Activity 19 - Restoration of Blurred Image. This last activity is about demonstration of restoration of a corrupted grayscale image with a known degradation function which in this case is motion blur and additive noise using Weiner filtering. The following schematic diagram is a model of the image degradation and restoration process. From the diagram, f hat(x, y). Here, h(x, y). Represents the degradation function, f(x, y). The power spect...
