Memetic Optimization of Video Chain Designs

Abstract. Improving image quality is the backbone of highly competitive display industry. Contemporary video processing system design is a challenging optimization problem. Generally, several video algorithms must be sequentially applied to real-time video data. Overall image quality depends on the nonlinear interactions between multiple design parameters: variable settings for each module (algorithm), the amount of data being transferred in the video processing chain as well as the order of the cascading modules. Unfortunately, no systematic techniques are currently available to configure the video chain without lengthy trial and error process. We propose a rapid and reliable method for optimization of composite video processing systems based on genetic algorithm coupled with local search heuristics. Video system configuration is evolved toward the best image quality, driven by an objective video quality metric. We analyze several local search approaches, including hill-climbing, simp...

• Type: Conference
• Year: 2004
• Where: GECCO
• Authors: Walid Ali, Alexander P. Topchy
• Keywords: GECCO 2004, Image Quality, Video, Video Processing