Online rate control in digital cameras for near-constant distortion based on minimum/maximum criterion

摘要

Abstract: We address the problem of online rate control in digital cameras, where the goal is to achieve near-constant distortion for each image. Digital cameras usually have a pre-determined number of images that can be stored for the given memory size and require limited time delay and constant quality for each image. Due to time delay restrictions, each image should be stored before the next image is received. Therefore, we need to define an online rate control that is based on the amount of memory used by previously stored images, the current image, and the estimated rate of future images. In this paper, we propose an algorithm for online rate control, in which an adaptive reference, a 'buffer-like' constraint, and a minimax criterion (as a distortion metric to achieve near-constant quality) are used. The adaptive reference is used to estimate future images and the 'buffer-like' constraint is required to keep enough memory for future images. We show that using our algorithm to select online bit allocation for each image in a randomly given set of images provides near constant quality. Also, we show that our result is near optimal when a minimax criterion is used, i.e., it achieves a performance close to that obtained by applying an off-line rate control that assumes exact knowledge of the images. Suboptimal behavior is only observed in situations where the distribution of images is not truly random (e.g., if most of the 'complex' images are captured at the end of the sequence.) Finally, we propose a T- step delay rate control algorithm and using the result of 1- step delay rate control algorithm, we show that this algorithm removes the suboptimal behavior. !10