A fast and efficient color image enhancement method based on fuzzy-logic and histogram

被引:64
作者
Raju, G. [1 ]
Nair, Madhu S. [2 ]
机构
[1] Kannur Univ, Sch Informat Sci & Technol, Kannur 670567, Kerala, India
[2] Mahatma Gandhi Univ, Sch Comp Sci, Kottayam 686560, Kerala, India
关键词
Contrast enhancement; Fuzzy logic; Histogram; Color images; Gray-level grouping; CONTRAST ENHANCEMENT; EQUALIZATION;
D O I
10.1016/j.aeue.2013.08.015
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A new fuzzy logic and histogram based algorithm for enhancing low contrast color images has been proposed here. The method is computationally fast compared to conventional and other advanced enhancement techniques. It is based on two important parameters M and K, where M is the average intensity value of the image, calculated from the histogram and K is the contrast intensification parameter. The given RGB image is converted into HSV color space to preserve the chromatic information contained in the original image. To enhance the image, only the V component is stretched under the control of the parameters M and K. The proposed method has been compared with conventional contrast enhancement techniques as well as with advanced algorithms. All the above techniques were based on the principle of transforming the skewed histogram of the original image into a uniform histogram. The performance of the different contrast enhancement algorithms are evaluated based on the visual quality, Tenengrad, CII and the computational time. The inter comparison of different techniques was carried out on different low contrast color images. Based on the performance analysis, we advocate that our proposed Fuzzy Logic method is well suited for contrast enhancement of low contrast color images. (C) 2013 Elsevier GmbH. All rights reserved.
引用
收藏
页码:237 / 243
页数:7
相关论文
共 24 条
[1]  
[Anonymous], 1999, IEEE T CONSUM ELECTR
[2]  
[Anonymous], 2006, Digital Image Processing
[3]   Shape preserving local histogram modification [J].
Caselles, V ;
Lisani, JL ;
Morel, JM ;
Sapiro, G .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 1999, 8 (02) :220-230
[4]   Image contrast enhancement based on a histogram transformation of local standard deviation [J].
Chang, DC ;
Wu, WR .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 1998, 17 (04) :518-531
[5]   Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation [J].
Chen, SD ;
Ramli, AR .
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2003, 49 (04) :1301-1309
[6]   Minimum mean brightness error bi-histogram equalization in contrast enhancement [J].
Chen, SD ;
Ramli, R .
IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2003, 49 (04) :1310-1319
[7]  
Choi YS, 1997, IEEE T IMAGE PROCESS, V6, P808, DOI 10.1109/83.585232
[8]   An optimal fuzzy system for color image enhancement [J].
Hamnandlu, Madasu ;
Jha, Devendra .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2006, 15 (10) :2956-2966
[9]  
Hanmandlu M, 1997, Biomed Sci Instrum, V33, P590
[10]  
JIMMERMANN HJ, 1991, FUZZY SET THEORY ITS