Computaional Photography portfolio
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Transcript of Computaional Photography portfolio
PHOTO-MOSAICnot ‘Pixel Perfect’, but ‘Picture Perfect’
Final Project
Slice Source image into tiles
Resize images from the image corpus keeping their aspect ratio
Find average brightness of each color channel of the corpus images
Compare the distance of the average brightness of each image with the average brightness of source image.
Replace each pixel in the source image with the image with the least distance
PHOTO-MOSAICnot ‘Pixel Perfect’, but ‘Picture Perfect’
Average Brightness
Median Brightness
Assignment #1A Photograph is a Photograph
Camera: NIKON COOLPIX S3100F-Stop: f/5.5
Exposure time: 1/1000 secISO speed: ISO-80
Focal length: 18mmExposure bias: 0 step
Max aperture: 3.4Metering Mode: Pattern
Flash Mode: No FlashDimension: 3240 X 4320
The Capitol
Assignment #2
Black and White
Used nested loop to traverse each pixel and checked the threshold value of 128. Value greater that 128 corresponded to 255 while the smaller one was changed to 0.
Horizontal Flip
Used nested loop to traverse each column in the image matrix. The (x,y) pixel values in each column was replaced with the value of (x, height-y) pixel value and stored in another 2D array.
Average of two images
Used nested loop to traverse the images and added the (x,y)th pixels of both the images and divided the values by 2. This was stored in a 2D array.
Assignment #3Epsilon Photography
Epsilon Photography
Ghosts on Road
Assignment #4Camera Obscura
The Setup
Pin Hole was created by covering the window.Pinhole
The Image
This wasn’t visible through eye but came up well on camera. The edges are not sharp since it was a big pin hole. The building specifics were not visible at all but the sky came out really good.
The Image
Assignment #5Gradients and Edges
X Gradient
For the X gradient, I subtracted the ith pixel from i+1th pixel looping through the columns.
For the Y gradient, I subtracted the ith pixel from i+1th pixel looping through the rows.
Y Gradient
Original image
Kernel image
Black and white imageThreshold - 100
Original image
Kernel image
Black and white imageThreshold - 150
Edge Detection
Assignment #6Blending
Output
Black
White
Mask
BlackWhite
Mask
Output Output
When converting the output to grayscale, it looks as It there is shadow of tree on the surface .
To create this mask, I took the Black image and using the threshold of 128 and changed the pixel value to 0 or 255
Black White Mask Output
Similarly I created masks for black image and tried to blend it with the white image.
I tried these with various threshold values to create masks and check the resultant blending.
Mask OutputMask Output
Assignment #7Feature Detection and Matching
Score: 3/10
Lighting
Score: 2/10
Rotation
Score: 4/10
Sample
Score: 10/10
Scale
Assignment #8Panorama
Sample Panorama created using inbuilt Phone feature
Assignment #9Photos of Space
PhotosynthFord Museum + Campionile
Site 2 (Campionile)
Link to Photosynth
PanoramaCampionile
PhotosphereCampionile + Labspace
Photosphere of Campionile
Photosphere of Labspace
Assignment #10HDR
Output with the given set of images
Output with the given set of images on the right.
Output with the given set of images on the right.
Assignment #11Video Textures
Output Link:https://drive.google.com/file/d/0B5Ncl02d4dOeS2JxeVIycEVMdmc/view?usp=sharing
https://drive.google.com/file/d/0B5Ncl02d4dOeNjVXS3BEa0pLeFU/view?usp=sharing