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Power consumption is very critical for portable video applications such as portable videophone and digital camcorder. Motion estimation (ME) in the video encoder requires a huge amount of computation, and hence consumes the largest portion of power. We propose a novel method of reducing power consumption of the ME by adaptively changing the pixel resolution during the computation of the motion vector. The pixel resolution is changed by masking or truncating the least significant bits of the pixel data, which is governed by the bit-rate control mechanism. Experimental results show that on average more than 4 bits ran be truncated without significantly affecting the picture quality. This results in more than 60% reduction in power consumption.

Power consumption is very critical for portable video applications such as portable video-phone. Motion estimation in the video encoder requires huge amount of computation and hence consumes the largest portion of power. In this paper we propose a novel method of reducing power consumption of the motion estimation by adaptively changing the pixel resolution during the computation of the motion vector. The pixel resolution is changed by masking or truncating the LSBs of the pixel data which is governed by an adaptive mechanism. Experimental results show that on average more than 4 bits can be truncated without affecting the picture quality. This results in an average 70% reduction in power consumption.

This paper presents a power evaluation framework designedfor estimating power consumption of a new video telephonecompression standard, ITU-H.263, at the system level.A hierarchical,mixed-level simulation environment is built andcycle-accurate power macro-modeling is used for the architecturalpower evaluation.Experimental results show the effectivenessof the proposed framework and models.

Power consumption is very critical for portable video applications. Motion estimation in the video encoder requires huge amount of computation and hence consumes the largest portion of power. This paper investigates the power consumption of different motion estimation architectures. Full search architectures were used as an example to illustrate the power consumption mechanism. The principle can be extended to other commonly used fast search architectures. The result of this study can serve as a guideline for the selection of the appropriate architecture for portable applications.