That looks like a lot of complicated math to convert an image to JPEG. I wonder since JPEG is such a ubiquitous format, there are custom assembly instructions to accomplish some of the steps.
yzliu567
Why is DCT here used in JPEG, in comparison to fourier transform used to frequency domain?
yzliu567
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yzliu567
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irina694
@ericyche I think the math is needed for the JPEG compression to transform the image block by block and be an efficient compression algorithm. One advantage is that the compression algorithm is easily parallelizable. Each basis of the transform matches the patter in the image. Instead of representing an image as NxM pixel values, we now represent the whole image as 64 pairs of coefficients from which we can reconstruct a very similar image, but that can be stored at a fraction of the original size.
BrianSantoso
This video explains DCT pretty well
https://www.youtube.com/watch?v=0me3guauqOU
That looks like a lot of complicated math to convert an image to JPEG. I wonder since JPEG is such a ubiquitous format, there are custom assembly instructions to accomplish some of the steps.
Why is DCT here used in JPEG, in comparison to fourier transform used to frequency domain?
[deleted]
[deleted]
@ericyche I think the math is needed for the JPEG compression to transform the image block by block and be an efficient compression algorithm. One advantage is that the compression algorithm is easily parallelizable. Each basis of the transform matches the patter in the image. Instead of representing an image as NxM pixel values, we now represent the whole image as 64 pairs of coefficients from which we can reconstruct a very similar image, but that can be stored at a fraction of the original size.
This video explains DCT pretty well https://www.youtube.com/watch?v=0me3guauqOU