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A quick description of Rate distortion theory. |
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We want to encode a video, picture or music optimally. |
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What does optimally mean? |
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It means that we want to get the best quality at a given |
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filesize OR (which is almost the same actually) We want to get the |
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smallest filesize at a given quality. |
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Solving this directly isnt practical, try all byte sequences |
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1MB long and pick the best looking, yeah 256^1000000 cases to try ;) |
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But first a word about Quality also called distortion, this can |
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really be almost any quality meassurement one wants. Commonly the |
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sum of squared differenes is used but more complex things that |
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consider psychivisual effects can be used as well, it makes no differnce |
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to us here. |
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First step, that RD factor called lambda ... |
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Lets consider the problem of minimizing |
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distortion + lambda*rate |
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for a fixed lambda, rate here would be the filesize, distortion the quality |
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Is this equivalent to finding the best quality for a given max filesize? |
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The awnser is yes, for each filesize limit there is some lambda factor for |
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which minimizing above will get you the best quality (in your provided quality |
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meassurement) at that (or a lower) filesize |
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Second step, spliting the problem. |
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Directly spliting the problem of finding the best quality at a given filesize |
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is hard because we dont know how much filesize to assign to each of the |
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subproblems optimally. |
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But distortion + lambda*rate can trivially be split |
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just consider |
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(distortion0 + distortion1) + lambda*(rate0 +rate1) |
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a problem made of 2 independant subproblems, the subproblems might be 2 |
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16x16 macroblocks in a frame of 32x16 size. |
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to minimize |
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(distortion0 + distortion1) + lambda*(rate0 +rate1) |
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one just have to minimize |
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distortion0 + lambda*rate0 |
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and |
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distortion1 + lambda*rate1 |
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aka the 2 problems can be solved independantly |
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Author: Michael Niedermayer |
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Copyright: LGPL |
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