摘要
通过航空传感器获得的高灰阶影像,灰度级范围往往会超过256,为了达到视觉识别的要求,需要对高灰阶的影像进行量化。量化的过程会造成数据信息的损失,如何有效地保留最大的信息量,确定影像量化的最优方法是本文研究的主要内容。影像的熵是衡量影像信息量的一个重要考量标准。本文通过引入复合熵和共轭熵等概念,详细阐述了确定高灰阶影像量化最优解的方法,并通过实验分析证明了理论的可行性。
High-gray-scale images,obtained by airborne sensor,has often more than 256 gray scales.In order to achieve the visual identification requirements,quantification for high gray scale image is needed.Because quantization process will cause data loss,how to retain the maximum amount of information effectively and determine the optimal method for image quantization is the main content of this paper.Image entropy is an important standard to measure the amount of image information.By introducing the concept of composite entropy and conjugate entropy,this paper elaborates the optimal solution method of high-gray-scale image quantization,and proves the feasibility of the theory by experiment analysis.
出处
《数码设计》
2017年第7期90-93,共4页
Peak Data Science
关键词
高灰阶影像
量化
熵
最优解
high gray scale
image quantization
entropy
optimal solution
