Showing posts with label YouTube. Show all posts
Showing posts with label YouTube. Show all posts

Sunday, April 5, 2015

Video Compression as Fast As Possible

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We need to compress video 

Video compression technologies are about reducing and removing redundant video data so that a digital video file can be effectively sent over a network and stored on computer disks.
Uncompressed video (and audio) data are huge.
The high bit rates that result from the various types of digital video make their transmission through their intended channels very difficult.

Lossy methods have employed since the compression ratio of lossless methods (e.g., Huffman, Arithmetic, LZW) is not high enough for image and video compression, especially when the distribution of pixel values is relatively flat.

The following compression types are commonly used in Video compression:
  • Spatial Redundancy Removal - Intraframe coding (JPEG)
  • Spatial and Temporal Redundancy Removal - Intraframe and Interframe coding (H.261, MPEG)

Sunday, October 26, 2014

Dilation simple image explanation



Morphology is a broad set of image processing operations that process images based on shapes. Morphological operations apply a structuring element to an input image, creating an output image of the same size. In a morphological operation, the value of each pixel in the output image is based on a comparison of the corresponding pixel in the input image with its neighbors. By choosing the size and shape of the neighborhood, you can construct a morphological operation that is sensitive to specific shapes in the input image.

The most basic morphological operations are dilation and erosion. Dilation adds pixels to the boundaries of objects in an image while erosion removes pixels on object boundaries. The number of pixels added or removed from the objects in an image depends on the size and shape of the structuring element used to process the image. In the morphological dilation and erosion operations, the state of any given pixel in the output image is determined by applying a rule to the corresponding pixel and its neighbors in the input image. The rule used to process the pixels defines the operation as a dilation or an erosion. This table lists the rules for both dilation and erosion.
source
http://in.mathworks.com/help/images/morphological-dilation-and-erosion.html?requestedDomain=www.mathworks.com

Sunday, August 4, 2013

8 Queens Problem animated resolution

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Tuesday, July 9, 2013

Intro to Computer Architecture

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