Fractional-Order Integration Based Fusion Model for Piecewise Gamma Correction Along With Textural Improvement for Satellite Images

被引:12
作者
Singh, Himanshu [1 ]
Kumar, Anil [1 ]
Balyan, L. K. [1 ]
Lee, Heung-No [2 ]
机构
[1] Indian Inst Informat Technol Design & Mfg Jabalpu, Jabalpur 482005, India
[2] Gwangju Inst Sci & Technol, Gwangju 500712, South Korea
基金
新加坡国家研究基金会;
关键词
Fractional-order (FO) masking filter; fractional-order integration (FOI); Riemann-Liouville (RL) definition; sine cosine algorithm (SCA); opposition-based learning (OBL); gray-level co-occurrence matrix (GLCM); quality enhancement; optimal mask designing; two-dimensional (2-D) adaptive filtering; piecewise-gamma correction (PGC); HISTOGRAM EQUALIZATION; ENHANCEMENT;
D O I
10.1109/ACCESS.2019.2901292
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Fractional-order integration (FOI) and its beauty of optimally ordered adaptive filtering for image quality enhancement are latently too valuable to be casually dismissed. With this motivation, a new Riemann-Liouville fractional-order calculus-based spatial-masking methodology is proposed in this paper in association with counterbalanced piecewise gamma correction (PGC). A generalized FOI-based mask is also suggested. This mask is negatively augmented with the original image for harvesting texture-based benefits. PGC is just employed through a constructive association of both kinds of reciprocally dual gamma values (gamma(1) = gamma and gamma(2) = 1/gamma, for all gamma > 1), which leads to optimally desired enhancement when applied in a weighted counter-correction manner. Efficiently improved and recently proposed opposition-based learning inspired sine-cosine algorithm is employed in this paper, along with a newly framed fitness function. This iftness function is devised in a novel manner by taking care of textural as well as non-textural details of the images. In this paper, especially for dark images, 130% increment is achieved over the input contrast along with the simultaneous 147% increment in the discrete entropy level and 22.8% increment in the sharpness content. Also, brightness and colorfulness are reported with 130% and 196.4% increased with respect to the input indices, respectively. In addition, the textural improvement is advocated in terms of desired comparative reduction of gray-level co-occurrence matrix-based metrics, namely, correlation, energy, and homogeneity, which are suppressed by 25.6%, 72.5%, and 21.8%, respectively. This performance evaluation underlines the excellence and robustness for imparting proper texture as well as edge preserved (or efficiently restored) image quality improvement.
引用
收藏
页码:37192 / 37210
页数:19
相关论文
共 16 条
[1]   An improved Opposition-Based Sine Cosine Algorithm for global optimization [J].
Abd Elaziz, Mohamed ;
Oliva, Diego ;
Xiong, Shengwu .
EXPERT SYSTEMS WITH APPLICATIONS, 2017, 90 :484-500
[2]   Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution [J].
Huang, Shih-Chia ;
Cheng, Fan-Chieh ;
Chiu, Yi-Sheng .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2013, 22 (03) :1032-1041
[3]   On the performance of artificial bee colony (ABC) algorithm [J].
Karaboga, D. ;
Basturk, B. .
Applied Soft Computing Journal, 2008, 8 (01) :687-697
[4]  
Kennedy J, 1995, 1995 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS PROCEEDINGS, VOLS 1-6, P1942, DOI 10.1109/icnn.1995.488968
[5]   Intensity and edge based adaptive unsharp masking filter for color image enhancement [J].
Lin, S. C. F. ;
Wong, C. Y. ;
Jiang, G. ;
Rahman, M. A. ;
Ren, T. R. ;
Kwok, Ngaiming ;
Shi, Haiyan ;
Yu, Ying-Hao ;
Wu, Tonghai .
OPTIK, 2016, 127 (01) :407-414
[6]   Image enhancement using the averaging histogram equalization (AVHEQ) approach for contrast improvement and brightness preservation [J].
Lin, S. C. F. ;
Wong, C. Y. ;
Rahman, M. A. ;
Jiang, G. ;
Liu, S. ;
Kwok, Ngaiming ;
Shi, Haiyan ;
Yu, Ying-Hao ;
Wu, Tonghai .
COMPUTERS & ELECTRICAL ENGINEERING, 2015, 46 :356-370
[7]   SCA: A Sine Cosine Algorithm for solving optimization problems [J].
Mirjalili, Seyedali .
KNOWLEDGE-BASED SYSTEMS, 2016, 96 :120-133
[8]   Fractional Differential Mask: A Fractional Differential-Based Approach for Multiscale Texture Enhancement [J].
Pu, Yi-Fei ;
Zhou, Ji-Liu ;
Yuan, Xiao .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2010, 19 (02) :491-511
[9]   Swarm intelligence optimized piecewise gamma corrected histogram equalization for dark image enhancement [J].
Singh, Himanshu ;
Kumar, Anil ;
Balyan, L. K. ;
Singh, G. K. .
COMPUTERS & ELECTRICAL ENGINEERING, 2018, 70 :462-475
[10]   Slantlet filter-bank-based satellite image enhancement using gamma-corrected knee transformation [J].
Singh, Himanshu ;
Kumar, A. ;
Balyan, L. K. ;
Singh, G. K. .
INTERNATIONAL JOURNAL OF ELECTRONICS, 2018, 105 (10) :1695-1715