کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
563491 875499 2012 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Multi-stage image denoising based on correlation coefficient matching and sparse dictionary pruning
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
پیش نمایش صفحه اول مقاله
Multi-stage image denoising based on correlation coefficient matching and sparse dictionary pruning
چکیده انگلیسی

We present a novel image denoising method based on multiscale sparse representations. In tackling the conflicting problems of structure extraction and artifact suppression, we introduce a correlation coefficient matching criterion for sparse coding so as to extract more meaningful structures from the noisy image. On the other hand, we propose a dictionary pruning method to suppress noise. Based on the above techniques, an effective dictionary training method is developed. To further improve the denoising performance, we propose a multi-stage sparse coding framework where sparse representations are obtained in different scales to capture multiscale image features for effective denoising. The multi-stage coding scheme not only reduces the computational burden of previous multiscale denoising approaches, but more importantly, it also contributes to artifact suppression. Experimental results show that the proposed method achieves a state-of-the-art denoising performance in terms of both objective and subjective quality and provides significant improvements over other methods at high noise levels.

Figure optionsDownload as PowerPoint slideHighlights
► Effective structure extraction with correlation coefficient matching.
► Dictionary pruning based on noise detection.
► Muti-stage sparse denoising with smooth thresholding.
► State-of-the-art denoising performance in terms of both objective and subjective quality.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing - Volume 92, Issue 1, January 2012, Pages 139–149
نویسندگان
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