Cost-Effective Implementation of Order-Statistics Based Vector Filters Using Minimax Approximations
Louisiana State University（路易斯安那州立大学）；Georgia Institute of Technology（佐治亚理工学院）；Epson Canada Ltd.（爱普生加拿大有限公司）；Wayne State University（韦恩州立大学）
英文摘要：
Vector operators based on robust order statistics have proved successful in digital multichannel imaging applications, particularly color image filtering and enhancement, in dealing with impulsive noise while preserving edges and fine image details. These operators often have very high computational requirements which limits their use in time-critical applications. This paper introduces techniques to speed up vector filters using the minimax approximation theory. Extensive experiments on a large and diverse set of color images show that proposed approximations achieve an excellent balance among ease of implementation, accuracy, and computational speed.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
