Dynamic Reconfiguration of Approximate Arithmetic Units for Image Encoding

Abstract

from the field of approximate computing has received significant attention, particularly in the context of different signal processing. Image and video compression algorithms such as JPEG, MPEG and so on, which can be exploited to realize highly power-efficient implementations of these algorithms. However, existing approximate architectures typically fix the level of hardware approximations statically and are not adaptive to input data. This project addresses this issue by proposing a reconfigurable approximate for MPEG encoders that optimizes power consumption with the aim of maintaining a particular peak signal-to-noise ratio threshold for any video.