| Summary: | Digital video is becoming an increasingly widespread application on a multitude of devices ranging from mobile devices to digital cinema. Technological advancements in processing speed and available bandwidth along with substantial improvements in compression techniques enable completely new applications and services for digital video content.
The most demanding task in video encoding is the motion estimation process which aims to identify similarities to previously transmitted video frames. Up to 90% of the processing requirements are attributable to this element.
In this thesis, we present three methods for encoding new and transcoding existing video content with significantly reduced computational complexity while maintaining both quality and bitrate.
The first method reduces the number of steps required to perform motion estimation by adaptively adjusting the search accuracy needed in distortion measurement.
The second method addresses the topic of mode decision in video encoding and provides an algorithm that allows an early decision about the most probable modes without the need to evaluate all 259 different combinations of block sizes.
The third method provides a multi-dimensional measure that facilitates evaluating only the most likely modes for efficiently transcoding existing pre-encoded content to lower resolutions with an arbitrary downscaling ratio. This is an important factor for the ever-growing number of devices and application scenarios that access existing pre-encoded content. Our method supplements existing fast transcoding schemes that primarily focus on efficiently determining motion vectors in transcoding. === Applied Science, Faculty of === Electrical and Computer Engineering, Department of === Graduate
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