image and video editing
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Various implementations of video and photo editing techniques which apply CUDA, Cheetah and MPI. Written for a problem set in Computer Science 205
at Harvard School of Engineering and Applied Sciences.
	
	image editing:
		1) sharpen:
			- applies a sharpening kernel to the interior pixels of an image 			with a sharpening coefficient of epsilon = 0.005 using a 9 point 			stencil
			- implemented with PyCUDA using 2D thread blocks and a 2D grid of 			blocks
			- mean and variance computed on the CPU
			- serial code and input photos provided by CS205 course staff (see 			documents in image_edit folder)
		2) region_grow:
			- applies a region growing algorithm to produce a black and white 			image that is clear and less noisy than using a simple dark filter
			- algorithm begins by finding seed points; then determines whether 			each pixel of the image should be added to the regions that grow 			from each seed and continues until no pixels were added in the last 			iteration
			- serial code and input photos provided by CS205 course staff (see 			documents in image_edit folder)

	video editing:
		- allows for application of any filter to a video 
		- the flexibility of the filter applied is implemented via Cheetah
		- similar algorithm as used in sharpen.py (described above) to apply 		filter to each frame of the movie clip
		- MPI used to access multiple GPU's in order to distribute application of 		filters to the various frames
		- serial code, video clip, and filters provided by CS205 course staff (see 		video_edit folder)