基于视觉特性和复杂度加权处理的图像增强新算法

被引：10

作者：

曾明

张建勋

王湘晖

陈少杰

机构：

[1] 南开大学机器人与信息自动化研究所

[2] 南开大学现代光学研究所

[3] 南开大学机器人与信息自动化研究所天津

[4] 天津

[5] 光电信息技术科学教育部国家重点实验室

来源：

光电子·激光 | 2005年 / 03期

关键词：

图像增强; 人眼视觉特性; 局部复杂度; 直方图;

D O I：

10.16136/j.joel.2005.03.027

中图分类号：

TP391.41 [];

学科分类号：

080203 ;

摘要：

针对经典直方图统计中的统计数据与信息量非相关问题,将局部复杂度加权处理应用到直方图构造中,在进行灰度级像素统计时,通过压缩平滑区的灰度级比重,解决统计数据信息量不一致问题,使得算法具有鲁棒性强,且对平滑区噪声抑制明显等优点。同时,为了优化配置主导灰度级动态范围,结合视觉系统感知特点,采用视觉分辨能力参数最佳视觉分辨偏差(OND)约束主导灰度级动态范围的方法,使得图像不仅获得了满意的视觉效果,同时有效地克服了振铃现象和噪声过增强等问题。

引用

页码：363 / 367

页数：5

共 10 条

[1]

A distortion measure for blocking artifacts in image based on human visual sensitivity. Karunsekera S A,Kingsbury N K. IEEE Transactions on Image Processing . 1995

[2]

Transform-based image enhancement algorithms with performance measure. Agaian S S,Panetta K,Grigoryan A M. IEEE Transactions on Image Processing . 2001

[3]

An analytical derivation of visual nonlinearity. Gershon B. IEEE Transations on Biomedical Engineering . 1980

[4]

A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile. Chou C H,Li Y C. IEEE Transactions on Circuits and Systems for Video Technology . 1995

[5]

Image contrast enhancement by constrained local histogram equalization. Zhu H,Chan H Y,Lam F K. Computer Vision and Image Understanding . 1999

[6]

Distortion criteria of the human viewer. John O L. IEEE Transactions on Systems Man and Cybernetics . 1979

[7]

An advanced contrast enhancement using partially overlapped sub-block histogram equalization. Kim J Y,Kim L S,Hwang S H. IEEE Transactions on Circuits and Systems for Video Technology . 2001

[8]

Contrast enhancement based on a novel homogeneity measurement. Cheng H D,Xue M,Shi X J. Pattern Recognition . 2003

[9]

Adaptive image contrast enhancement based on human visual properties. Ji T L,Sundareshan M K,Roehrig H. IEEE Transactions on Medical Imaging . 1994

[10]

A cubic unsharp masking technique for contrast enhancement. Ramponi G. Signal Processing . 1998

← 1 →