The Design of Hausdorff Measure－Based Image Classifier

樊国良; 周利华

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The Design of Hausdorff Measure－Based Image Classifier

更新时间：2025-12-08

- The Design of Hausdorff Measure－Based Image Classifier
- Acta Electronica Sinica Issue 11, (1997)
- 作者机构：
  
  西安电子科技大学计算机学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391.4
- Published：1997
- 稿件说明：
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[1]樊国良,周利华.基于Hausdorff测度的图像分类器设计[J].电子学报,1997(11):120-123.

樊国良, 周利华. The Design of Hausdorff Measure－Based Image Classifier[J]. Acta Electronica Sinica, 1997, (11).
[1]樊国良,周利华.基于Hausdorff测度的图像分类器设计[J].电子学报,1997(11):120-123. DOI：

樊国良, 周利华. The Design of Hausdorff Measure－Based Image Classifier[J]. Acta Electronica Sinica, 1997, (11). DOI：

摘要

本文采用基于Ｈａｕｓｄｏｒｆｆ测度的分类方法为分类静止图像编码算法设计了一种有效的图像块分类器，根据图像块的内部特征将其分为四大类：平坦区（Ｓｈａｄｅ），中间区（Ｍｉｄｒａｎｇｅ），边缘区（Ｅｄｇｅ），混合区（Ｍｉｔｅｄ），引入分形参数进行的定量分析增强了分类的通用性并改进了分类效果．同时，在一定的假设条件下，根据视觉熵（ＶＥ）的概念和人的视觉系统（ＨＶＳ）特性从第四类一Ｍｉｘｅｄ块中进一步分离出两种特殊区域一兴趣焦点（Ｋｅｙ－ｐｏｉｎｔ）和随机纹理区（Ｒａｎｄｏｍ－ｔｅｘｔｕｒｅ），使在主观视觉质量意义上，编码策略的最佳安排和编码系数的合理比特率分配成为可能．

Abstract

A common image classifier for classified still image coding scheme is designed based on Hausdoff-Measure

by which the image blocks can be grouped into four basic ciasses-Shade

Midrange

Edge and Mited. The introduction of fractal parameters improves the result of ciassification Meanwhile

under certain assumptions and with consideration of Visual Entropy and the characteristies of Human Visual System

two special categories

Key-point and Random-Texture

can be extracted from the fourth groupMixed

which makes possible optimal arrangement of image coding scheme and allocation of bitrate for coefficients in the meaning of subjective visual quality for decoded images.

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