A fast rate-distortion analytical framework for the PSNR-based optimization of JPEG baseline compression on color images is proposed in this paper. The analysis is conducted in th...
Our goal is to analyze regularized image reconstruction methods such as penalized likelihood with respect to the performance of the Channelized Hotelling Observer (CHO) in the tas...
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
An important problem in image labeling concerns learning with images labeled at varying levels of specificity. We propose an approach that can incorporate images with labels drawn...
Image segmentation is the first stage of processing in many practical computer vision systems. While development of particular segmentation algorithms has attracted considerable re...