کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
734414 1461641 2014 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Blind noisy image quality evaluation using a deformable ant colony algorithm
ترجمه فارسی عنوان
با استفاده از یک الگوریتم کلونی مورچه تغییر شکل داده، تصویر کافی را کنترل می کند
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی برق و الکترونیک
چکیده انگلیسی


• We evaluate image quality without the knowledge of the ground truth image.
• We propose a deformable ant colony optimization approach.
• We adaptively adjust the ant size for image block selection.

The objective of blind noisy image quality assessment is to evaluate the quality of the degraded noisy image without the knowledge of the ground truth image. Its performance relies on the accuracy of the noise statistics estimated from homogenous blocks. The major challenge of block-based approaches lies in the block size selection, as it affects the local noise derivation. To tackle this challenge, a deformable ant colony optimization (DACO) approach is proposed in this paper to adaptively adjust the ant size for image block selection. The proposed DACO approach considers that the size of the ant is adjustable during foraging. For the smooth image blocks, more pheromone is deposited, and then the size of ant is increased. Therefore, this strategy enables the ants to have dynamic food-search capability, leading to more accurate selection of homogeneous blocks. Furthermore, the regression analysis is used to obtain image quality score by exploiting the above-estimated noise statistics. Experimental results are provided to justify that the proposed approach outperforms conventional approaches to provide more accurate noise statistics estimation and achieve a consistent image quality evaluation performance for both the artificially generated and real-world noisy images.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Optics & Laser Technology - Volume 57, April 2014, Pages 265–270
نویسندگان
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