Autonomic image sequence processing

Issue title: Autonomous Computing

Guest editors: Elizabeth Chang, Manish Parashar, Roy Sterritt, Huaglory Tianfield and Rainer Unland

Article type: Research Article

Authors: Nichols, Jim | Bapty, Ted^{; *}

Affiliations: Institute for Software Integrated Systems, Box 1829, Station B, Vanderbilt University, Nashville, TN 37235, USA. E-mail: [email protected]; [email protected]

Correspondence: [*] Corresponding author.

Abstract: Implementing image-processing systems can require significant effort and resources due to information volume and algorithm complexity. Autonomic behavior is required for many image processing systems to perform consistently under real-world conditions. Model Integrated Computing (MIC) based image processing systems show promise in supporting solutions of these complex problems. While MIC has contributed to the advancement of performing complex image processing tasks on parallel-embedded systems, it has not addressed a challenging class of algorithms that adapt the image-processing algorithm based on the information or state of the image processing system. This paper addresses creating an autonomically grounded image-processing structure and environment based on MIC that allows solutions of complex image processing problems to be built and executed rapidly. The framework involves creating a new modeling representation for image processing adaptation mechanisms within a structure that allows growth in complexity and integration of autonomic constraints. The proposed MIC-based autonomically grounded image-processing environment will generate a solution given the modeling constraints and execute it on a number of hardware architectures.

DOI: 10.3233/ICA-2006-13103

Journal: Integrated Computer-Aided Engineering, vol. 13, no. 1, pp. 23-40, 2006