DCT cs195g: Computational Photography James Hays, Brown, Spring 2010 Somewhere in Cinque Terre, May 2005 Slides from Alexei Efros.

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Presentation transcript:

DCT cs195g: Computational Photography James Hays, Brown, Spring 2010 Somewhere in Cinque Terre, May 2005 Slides from Alexei Efros

Campbell-Robson contrast sensitivity curve

Depends on Color R GB

Lossy Image Compression (JPEG) Block-based Discrete Cosine Transform (DCT)

Using DCT in JPEG The first coefficient B(0,0) is the DC component, the average intensity The top-left coeffs represent low frequencies, the bottom right – high frequencies

Image compression using DCT DCT enables image compression by concentrating most image information in the low frequencies Loose unimportant image info (high frequencies) by cutting B(u,v) at bottom right The decoder computes the inverse DCT – IDCT Quantization Table

Block size in JPEG Block size small block –faster –correlation exists between neighboring pixels large block –better compression in smooth regions It’s 8x8 in standard JPEG

JPEG compression comparison 89k12k