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Who invented discrete cosine transform?
Nasir Ahmed
Nasir Ahmed (born 1940 in Bangalore, India) is an Indian-American electrical engineer and computer scientist. He is Professor Emeritus of Electrical and Computer Engineering at University of New Mexico (UNM). He is best known for inventing the discrete cosine transform (DCT) in the early 1970s.
What is discrete sine transform in image processing?
Discrete Sine Transform (DST) converts this digital information into its equivalent frequency domain by partitioning image pixel matrix into blocks of size N*N, N depends upon the type of image.
How is the discrete cosine transform used in trignometric functions?
The mechanism that we’ll be using for decomposing the image data into trignometric functions is the Discrete Cosine Transform . In this post, I won’t be going deep into how the math works, and will be a little hand-wavy, so if you’re interested in going further, the wikipedia page is a great starting point.
How is the DCT related to the cosine transform?
The DCT is a linear transformation that transforms a vector of length n containing “amplitudes”, and returns a different vector of length n containing the coefficients for n different cosine functions. Therefore, it is encoded by an n x n matrix, in which each row corresponds with a cosine function of a different frequency. Why use n cosine waves?
Why is the discrete cosine transform not invertibile?
If used fewer or greater than n cosine functions, then we would not be able to represent the transformation as a square matrix, and it would therefore not be invertibile, which is the key to being able to get our data back in terms of amplitudes after converting it to cosine coefficients.
Which is the most common variant of the discrete cosine transform?
The most common variant of discrete cosine transform is the type-II DCT, which is often called simply “the DCT”. Its inverse, the type-III DCT, is correspondingly often called simply “the inverse DCT” or “the IDCT”.