کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
529540 | 869672 | 2012 | 15 صفحه PDF | دانلود رایگان |
Noise estimation is an important process in digital imaging systems. Many noise reduction algorithms require their parameters to be adjusted based on the noise level. Filter-based approaches of image noise estimation usually were more efficient but had difficulty on separating noise from images. Block-based approaches could provide more accurate results but usually required higher computation complexity. In this work, a design framework for combining the strengths of filter-based and block-based approaches is presented. Different homogeneity analyzers for identifying the homogeneous blocks are discussed and their performances are compared. Then, two well-known filters, the bilateral and the non-local mean, are reviewed and their parameter settings are investigated. A new bilateral filter with edge enhancement is proposed. A modified non-local mean filter with much less complexity is also present. Compared to the original non-local mean filter, the complexity is dramatically reduced by 75% and yet the image quality is maintained.
► A design framework for hybrid approaches of image noise estimation was proposed.
► Different operators were investigated and shown to be good homogeneity analyzers.
► The proposed framework can provide accurate and reliable estimation of image noise.
► A modified bilateral filter was proposed to remove image noise and preserve edges.
► A modified non-local mean filter was proposed to reduce the complexity.
Journal: Journal of Visual Communication and Image Representation - Volume 23, Issue 5, July 2012, Pages 812–826