Title :
An adaptive motion estimation scheme using maximum mutual information criteria
Author :
Jing Zhao ; Erdogmus, Deniz ; Cancan Huang ; Dapeng Wu ; Yuguang Fang
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Florida, Gainesville, FL, USA
Abstract :
Motion estimation in video coding can be formulated as an optimization problem. Recently, a motion estimation scheme that uses Renyi´s error entropy as the optimization criterion, was proposed [1]. Motivated by [1], in this paper, we propose a different criterion in motion estimation, i.e., the criterion of maximum mutual information. Based on this new criterion, we design a motion estimation algorithm. Our results show that our algorithm achieves significantly lower computational complexity compared to existing fast-search methods for motion estimation. A salient feature of our algorithm is that it is ideally suited for wireless video sensor networks where limited bandwidth, restricted computational capability, and limited battery power supply pose stringent constraints on the system.
Keywords :
adaptive estimation; computational complexity; entropy; error analysis; motion estimation; optimisation; video coding; wireless sensor networks; Renyi error entropy; adaptive motion estimation scheme; computational complexity; maximum mutual information criteria; optimization criterion; optimization problem; video coding; wireless video sensor network; Adaptive systems; Complexity theory; Decoding; Entropy; Motion estimation; Mutual information; Vectors;
Conference_Titel :
Signal Processing Conference, 2005 13th European
Conference_Location :
Antalya
Print_ISBN :
978-160-4238-21-1