Image Enhancement Based on Wavelet Transform and Contrast Limited Adaptive Histogram Equalization

YU Tian-he; MENG Xue; PAN Ting; LAN Chao-feng

doi:10.15938/j.jhust.2018.06.018

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Image Enhancement Based on Wavelet Transform and Contrast Limited Adaptive Histogram Equalization

更新时间：2026-08-31

- Image Enhancement Based on Wavelet Transform and Contrast Limited Adaptive Histogram Equalization
- Vol. 23, Issue 6, Pages: 100-104(2018)
- 作者机构：
  
  哈尔滨理工大学电气与电子工程学院,黑龙江,哈尔滨,150080
- 作者简介：
- 基金信息：
- DOI：10.15938/j.jhust.2018.06.018
  CLC： TP391
- Published：2018
- 稿件说明：
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YU Tian-he, MENG Xue, PAN Ting, et al. Image Enhancement Based on Wavelet Transform and Contrast Limited Adaptive Histogram Equalization[J]. 2018, 23(6): 100-104.
DOI：

YU Tian-he, MENG Xue, PAN Ting, et al. Image Enhancement Based on Wavelet Transform and Contrast Limited Adaptive Histogram Equalization[J]. 2018, 23(6): 100-104. DOI： 10.15938/j.jhust.2018.06.018.

摘要

摘要:对比度受限的自适应直方图均衡是一种提高图像的局部细节有效的算法(简称为自适应变换CLAHE)。针对它在应用过程中存在对比度和过度拉伸噪声增强问题，提出了一种有效的图像增强方法，命名为CLAHE离散小波变换，它结合了CLAHE与离散小波变换。首先，原始图像由离散小波变换分解为低频和高频部分。然后，分别使用CLAHE增强低频系数和对高频带小波系数进行滤波，以限制噪声增强。这是因为高频分量对应于细节信息，低频部分包含雾霾图象的大部分噪声。最后，通过采取新的系数小波逆变换重建图像。

Abstract

Abstract:Contrast limited adaptive histogram equalization (CLAHE) is an efficient algorithm to improve the local details of an image In this paper

we propose an image enhancement method named CLAHE Discrete Wavelet Transform to solve the problem of contrast and overstretched noise in the application process，which combines CLAHE and discrete wavelet transform This method consists of three major steps: First

the original image is decomposed into low frequency and high frequency by the discrete wavelet transform Then

the low frequency coefficients are enhanced by CLAHE and the high frequency coefficients is filtered to limit the noise enhancement This is because the highfrequency component corresponding to the details

the low frequency portion comprises most of the noise image haze Finally

reconstruct the image by taking inverse discrete wavelet transform of the new coefficients

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