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

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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...

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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.

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Liknayang Inaplay 186: September 2009

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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...

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Liknayang Inaplay 186: August 2009

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Gilbert's Applied Physics 186 Blog. Thursday, August 27, 2009. Activity 15 - Probabilistic Classification. This activity is similar to the previous one except that another method is implemented here. Objects are grouped here using probabilistic classification. Instead of 3, only 2 classes are considered here which are all from Activity 14. Rice crackers and Superthin. Biscuits. As assembled previously, 10 samples represent each class. These are shown below. Is assigned to class i. That has maximum f i.

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Liknayang Inaplay 186: July 2009

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Gilbert's Applied Physics 186 Blog. Thursday, July 30, 2009. Activity 11 - Color Image Processing. After previous activities of processing grayscale and binary-type images, this time, color images are handled here specifically true color images which are taken by a digital color camera using its various white balancing (WB) settings. From the expressions above, rho. Corresponds to the spectral reflectance of a surface, S. Is the spectral sensitivity of a color camera in the RGB channels. Meanwhile, K.

thejaggernaut.blogspot.com

Master's Piece: August 2009

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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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Master's Piece: July 2009

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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...

ccesporlas-ap186.blogspot.com

CINDY 186: September 2009

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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. The human brain m...

ccesporlas-ap186.blogspot.com

CINDY 186: October 2009

http://ccesporlas-ap186.blogspot.com/2009_10_01_archive.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...