Low Complexity Situational Models in Image Quality Improvement

Várkonyi-Kóczy, Annamária R.

doi:10.1007/978-3-642-11739-8_8

Cited by 1 publication

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References 12 publications

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“…It is expected that a fuzzy approach can represent a more powerful resource. Indeed, fuzzy techniques are well suited to model the uncertainty that occurs when conflicting tasks are performed, for example, noise cancellation and detail preservation [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

A fuzzy approach to performance measurement of grayscale image denoising algorithms

Russo

2015

2015 IEEE 9th International Symposium on Intelligent Signal Processing (WISP) Proceedings

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The most advanced metrics for performance evaluation of image denoising algorithms are based on the classification of filtered pixels in two crisp classes: pixels where residual noise is still present (due to insufficient filtering) and pixels where excessive filtering has produced distortion. However, the intrinsic nature of image denoising is very likely to be fuzzy: a pixel can be affected by different degrees of unfiltered noise and filtering distortion as well. According to this idea, a new method for performance measurement of grayscale image denoising filter is presented. The method adopts a fuzzy modelbased procedure that estimates, for each filtered pixel, the different components of the filtering error, i.e., the amounts of unfiltered noise and filtering distortion produced by the denoising process. Computer simulations dealing with different test images corrupted by various amounts of noise show that the new approach performs significantly better than state-of-the art metrics in the field. Furthermore, the results yielded by the proposed method are in perfect agreement with the true values of residual noise and image blur that can be theoretically evaluated for an important class of denoising filters.

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Section: Introductionmentioning

confidence: 99%

A fuzzy approach to performance measurement of grayscale image denoising algorithms

Russo

2015

2015 IEEE 9th International Symposium on Intelligent Signal Processing (WISP) Proceedings

View full text Add to dashboard Cite

show abstract

Low Complexity Situational Models in Image Quality Improvement

Cited by 1 publication

References 12 publications

A fuzzy approach to performance measurement of grayscale image denoising algorithms

A fuzzy approach to performance measurement of grayscale image denoising algorithms

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