Analog parallel processor solutions for video encoding

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Koskinen, Lauri
dc.date.accessioned 2012-02-17T07:26:27Z
dc.date.available 2012-02-17T07:26:27Z
dc.date.issued 2005-12-16
dc.identifier.isbn 951-22-7959-2
dc.identifier.issn 1455-8440
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/2649
dc.description.abstract This thesis deals with Cellular Nonlinear Network (CNN) analog parallel processor networks and their implementations in current video coding standards. The target applications are low-power video encoders within 3rd generation mobile terminals. The video codecs of such mobile terminals are defined by either the MPEG-4/H.263 or H.264 video standard. All of these standards are based on the block-based hybrid approach. As block-based motion estimation (ME) is responsible for most of the power consumption of such hybrid video encoders, this thesis deals mostly with low-power ME implementations. Low-power solutions are introduced at both the algorithmic and hardware levels. On the algorithmic level, the introduced implementations are derived from a segmentation algorithm, which has previously been partly realized. The first introduced algorithm reduces the computational complexity of ME within an object-based MPEG-4 encoder. The use of this algorithm enables a 60% drop in the power consumption of Full Search ME. The second algorithm calculates a near-optimal block-size partition for H.264 motion estimation. With this algorithm, the use of computationally complex Lagrange optimization in H.264 ME is not required. The third algorithm reduces the shape bit-rate of an object-based MPEG-4 encoder. On the hardware level a CNN-type ME architecture is introduced. The architecture includes connections and circuitry to fully realize block-based ME. The analog ME implemented with this architecture is capable of lower power than comparable digital realizations. A 9×9 test chip has also been realized. Additionally implemented is a digital predictive ME realization that takes advantage of the introduced partition algorithm. Although the IC layout of the ME algorithm was drawn, the design was verified as an FPGA. en
dc.format.extent 133
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Helsinki University of Technology en
dc.publisher Teknillinen korkeakoulu fi
dc.relation.ispartofseries Report / Helsinki University of Technology, Department of Electrical and Communications Engineering, Electronic Circuit Design Laboratory en
dc.relation.ispartofseries 41 en
dc.subject.other Electrical engineering en
dc.title Analog parallel processor solutions for video encoding en
dc.type G4 Monografiaväitöskirja fi
dc.description.version reviewed en
dc.contributor.department Department of Electrical and Communications Engineering en
dc.contributor.department Sähkö- ja tietoliikennetekniikan osasto fi
dc.subject.keyword motion estimation en
dc.subject.keyword cellular neural/nonlinear networks en
dc.subject.keyword MPEG-4 en
dc.subject.keyword H.264 en
dc.subject.keyword parallel processing en
dc.identifier.urn urn:nbn:fi:tkk-006093
dc.type.dcmitype text en
dc.type.ontasot Väitöskirja (monografia) fi
dc.type.ontasot Doctoral dissertation (monograph) en
dc.contributor.lab Electronic Circuit Design Laboratory en
dc.contributor.lab Piiritekniikan laboratorio fi


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