کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4962939 1446999 2017 39 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Modified differential evolution algorithm for contrast and brightness enhancement of satellite images
ترجمه فارسی عنوان
الگوریتم اصلاح شده الگوریتم تکاملی برای افزایش کنتراست و روشنایی تصاویر ماهواره ای
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Satellite images normally possess relatively narrow brightness value ranges necessitating the requirement for contrast stretching, preserving the relevant details before further image analysis. Image enhancement algorithms focus on improving the human image perception. More specifically, contrast and brightness enhancement is considered as a key processing step prior to any further image analysis like segmentation, feature extraction, etc. Metaheuristic optimization algorithms are used effectively for the past few decades, for solving such complex image processing problems. In this paper, a modified differential Modified Differential Evolution (MDE) algorithm for contrast and brightness enhancement of satellite images is proposed. The proposed algorithm is developed with exploration phase by differential evolution algorithm and exploitation phase by cuckoo search algorithm. The proposed algorithm is used to maximize a defined fitness function so as to enhance the entropy, standard deviation and edge details of an image by adjusting a set of parameters to remodel a global transformation function subjective to each of the image being processed. The performance of the proposed algorithm is compared with ten recent state-of-the-art enhancement algorithms. Experimental results demonstrate the efficiency and robustness of the proposed algorithm in enhancing satellite images and natural scenes effectively. Objective evaluation of the compared methods was done using several full-reference and no-reference performance metrics. Qualitative and quantitative evaluation results proves that the proposed MDE algorithm outperforms others to a greater extend.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Soft Computing - Volume 61, December 2017, Pages 622-641
نویسندگان
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