A generalized Masi entropy based efficient multilevel thresholding method for color image segmentation
- 54 Downloads
Multilevel thresholding for image segmentation is a crucial process in several applications such as feature extraction and pattern recognition. In this paper, a novel Masi entropy-based criterion for color satellite image multilevel thresholding is proposed. The proposed algorithm is based on Masi entropy which can deal with the additive/non-extensive information through the aid of a concordant entropic parameter ‘r’ which is extended in favor of multilevel based color satellite image segmentation. In addition, a comparative study between proposed Masi entropy-based color image multilevel thresholding and well known state-of-the-art entropies such as Kapur’s, Renyi’s and Tsallis entropy is presented. The simulation results of the proposed Masi entropy-based algorithm illustrate better performance for normal and color satellite image segmentation. Trials are conducted on various color test images to concrete the efficiency of the proposed algorithm. For segmentation purpose numerous fidelity parameters are computed such as structural similarity index (SSIM), feature similarity index (FSIM), misclassification error (ME), mean square error (MSE) and peak signal to noise ratio (PSNR).
KeywordsEfficient multilevel thresholding Color image segmentation Kapur’s Renyi’s Tsallis and Masi’s entropy
The authors wish to thank all reviewers and associate editor for their fruitful comments and suggestions for significant improvement of the manuscript. We thank Mr. Mohit Kumar, Assistant Professor (Muzaffarpur Institute of Technology, Muzaffarpur, Bihar) for editing the English text of a draft of this manuscript.
- 2.Bhandari AK (2018) A novel beta differential evolution algorithm-based fast multilevel thresholding for color image segmentation. Neural Computing and Applications 1–31Google Scholar
- 11.Bhandari AK, Maurya S, Meena AK (2018) Social spider optimization based optimally weighted Otsu thresholding for image enhancement. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 1–13Google Scholar
- 13.Chao Y, Dai M, Chen K, Chen P, Zhang Z (2016) A novel gravitational search algorithm for multilevel image segmentation and its application on semiconductor packages vision inspection. Optics 127(14):5770–5782Google Scholar
- 17.Han B, Wu Y, Song Y (2017) A novel active contour model based on median absolute deviation for remote sensing river image segmentation. Computers & Electrical EngineeringGoogle Scholar
- 21.Kaur T, Saini BS, Gupta S (2016) Optimized multi threshold brain tumor image segmentation using two dimensional minimum cross entropy based on co-occurrence matrix. In Medical Imaging in Clinical Applications (pp. 461–486). Springer International PublishingGoogle Scholar
- 29.Pare S, Bhandari AK, Kumar A, Bajaj V (2017) Backtracking search algorithm for color image multilevel thresholding. SIViP:1–8Google Scholar
- 32.Pare S, Bhandari AK, Kumar A, Singh GK (2019) Rényi’s entropy and Bat algorithm based color image multilevel thresholding. In: Machine Intelligence and Signal Analysis (pp. 71–84). Springer, SingaporeGoogle Scholar
- 33.Pare S, Bhandari AK, Kumar A, Singh GK, Khare S (2015). Satellite image segmentation based on different objective functions using genetic algorithm: a comparative study. In Digital Signal Processing (DSP), 2015 IEEE International Conference on (pp. 730–734). IEEEGoogle Scholar
- 44.The Berkeley Segmentation Dataset and Benchmark (2018) https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/bsds/