基于小波分頻與直方圖均衡的圖像增強算法

摘 要:傳統(tǒng)直方圖均衡化算法在增強圖像的同時也丟失了圖像細節(jié)、增強了圖像的噪聲信號，導致信息熵下降。結(jié)合小波變換多尺度、多分辨率的特點和直方圖均衡的優(yōu)勢，提出一種基于小波分頻和直方圖均衡的高亮度圖像增強算法。首先利用小波變換將圖像分解為低頻分量和高頻分量，然后僅對低頻分量做直方圖均衡處理，再由均衡后的低頻分量與各高頻分量進行小波重構(gòu)。實驗結(jié)果表明，該算法對于亮度較高的灰度圖像有較好的增強效果。關(guān)鍵詞:圖像增強; 小波變換; 小波分頻; 直方圖均衡

中圖分類號:TN911.73-34文獻標識碼:A

文章編號:1004-373X(2010)16-0149-02

Image Enhancement Algorithm Based on Wavelet Frequency Division Histogram Equalization

ZHENG Hui， WU Jin

(School of Information Science and Engineering， Wuhan University of Science and Technology， Wuhan 430080， China)

Abstract: The traditional histogram equalization processing algorithm lost image details and enhanced noise signal while it enhanced image， which led to the descent of information entropy. A high brightness image enhancement algorithm based on wavelet frequency division and histogram equalization is put forward in combination with the characteristics of multi-scale and multi-resolution of wavelet transform and the predominance of histogram equalization. At first， the image is divided into the low frequency parts and the high frequency parts， and histogram equalization processing is only applied to the low frequency parts. Then， the wavelet is reconstituted by the low frequency parts which have been equalized with the original high frequency parts. The experimental results show that this algorithm can enhance image of high brightness effectively.Keywords: image enhancement; wavelet transform; wavelet frequency division; histogram equalization

圖像增強技術(shù)是一類基本的圖像處理技術(shù)，是指有選擇地突出圖像中感興趣的特征或者抑制圖像中某些不需要的特征，其目的是使處理后的圖像更適合于人的視覺特性或機器的識別系統(tǒng)，包括圖像的輪廓線或者紋理加強、圖像去噪、對比度增強等。因此圖像增強處理是圖像分析和圖像理解的前提和基礎(chǔ)[1]。在圖像的獲取過程中，特別是對于多媒體監(jiān)控系統(tǒng)采集的圖像，由于監(jiān)控場景光線照射復雜、拍攝背景也比較復雜等環(huán)境因素的影響。加之攝像設(shè)備、傳感器等因素引入的噪聲，使監(jiān)控圖像在一定程度上存在對比度差、灰度分布范圍窄、圖像分辨率下降。因此.為得到一幅清晰的圖像.必須進行增強處理。傳統(tǒng)的圖像增強算法通常是基于整幅圖像的統(tǒng)計量，這樣在計算整幅圖像的變換時，圖像中的低頻信息、高頻信息以及含有的噪聲，同時進行了變換，因而在增強圖像的同時也增強了噪聲，導致信息熵下降，給監(jiān)控圖像的分析和后期處理帶來了困難。……