کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
532075 869903 2014 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A general non-local denoising model using multi-kernel-induced measures
ترجمه فارسی عنوان
یک مدل انحصاری عمومی غیر محلی با استفاده از اقدامات ناشی از چند هسته
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی


• We propose a general non-local denoising model which is multi-kernel induced and robust.
• Show that NLM filter and the lately proposed MNF filter are both its special cases.
• Extend the two typical filters to their advanced counterparts by means of the model.

Noises are inevitably introduced in digital image acquisition processes, and thus image denoising is still a hot research problem. Different from local methods operating on local regions of images, the non-local methods utilize non-local information (even the whole image) to accomplish image denoising. Due to their superior performance, the non-local methods have recently drawn more and more attention in the image denoising community. However, these methods generally do not work well in handling complicated noises with different levels and types. Inspired by the fact in machine learning field that multi-kernel methods are more robust and effective in tackling complex problems than single-kernel ones, we establish a general non-local denoising model based on multi-kernel-induced measures (GNLMKIM for short), which provides us a platform to analyze some existing and design new filters. With the help of GNLMKIM, we reinterpret two well-known non-local filters in the united view and extend them to their novel multi-kernel counterparts. The comprehensive experiments indicate that these novel filters achieve encouraging denoising results in both visual effect and PSNR index.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 47, Issue 4, April 2014, Pages 1751–1763
نویسندگان
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