کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8960126 | 1646381 | 2018 | 24 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Framelet regularization for uneven intensity correction of color images with illumination and reflectance estimation
ترجمه فارسی عنوان
تنظیم فرمالدهی برای اصلاح شدت ناهموار تصاویر رنگی با برآورد روشنایی و بازتاب
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
To solve the problem of simultaneously estimating the illumination and reflectance (IR) from a single image based on the Retinex theory, an effective way is utilizing a Maximum-a-Posterior (MAP) distribution as an approximation. However, the current MAP-based image enhancement methods fail to fully utilize the property of the reflectance, which leads to the loss of detailed structures of images. Through a large number of observations, it is found that the properties of reflectance can be effectively extracted by a powerful operator called framelet transform. Therefore, we propose a novel image enhancement scheme with framelet regularization on the reflectance, which is able to simultaneously estimate the IR while keeping image details. To be specific, a MAP distribution is adopted where a framelet regularization is proposed as a prior to exploiting the multi-scale edge information and sparsity of reflectance. Then the MAP problem is converted to a minimization of an energy function, which can be efficiently solved by an alternating direction method of multipliers with split Bregman iteration (ADMM-SBI). Furthermore, an adaptive Gamma correction operator is proposed to avoid over-enhancement of the illumination. Experiments show that the proposed approach outperforms the state-of-the-arts in terms of brightness improvement, contrast enhancement and details preservation.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 314, 7 November 2018, Pages 154-168
Journal: Neurocomputing - Volume 314, 7 November 2018, Pages 154-168
نویسندگان
Zhenghua Huang, Likun Huang, Qian Li, Tianxu Zhang, Nong Sang,