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An Adaptive Boosting Algorithm for Image Denoising

Zhuang Fang, Xuming Yi, Liming Tang
2019 Mathematical Problems in Engineering  
Image denoising is an important problem in many fields of image processing.  ...  Boosting algorithm attracts extensive attention in recent years, which provides a general framework by strengthening the original noisy image.  ...  Acknowledgments This work was supported in part by the National Natural Science Foundation of China under Grant Nos. 11671307, 61561019, 61763009, and 11761030 and by Doctoral Scientific  ... 
doi:10.1155/2019/8365932 fatcat:av6xplz27repbmqsrvecrurjni

Boosting of Image Denoising Algorithms [article]

Yaniv Romano, Michael Elad
2015 arXiv   pre-print
We demonstrate the SOS boosting algorithm for several leading denoising methods (K-SVD, NLM, BM3D, and EPLL), showing tendency to further improve denoising performance.  ...  The convergence of this process is studied for the K-SVD image denoising and related algorithms.  ...  SOS Boosting with state-of-the-art algorithms. The proposed SOS boosting is applicable to a wide range of denoising algorithms.  ... 
arXiv:1502.06220v2 fatcat:jkv6oplg6vhali4bhlgoof4hse

Boosting of Image Denoising Algorithms

Yaniv Romano, Michael Elad
2015 SIAM Journal of Imaging Sciences  
We demonstrate the SOS boosting algorithm for several leading denoising methods (K-SVD, NLM, BM3D, and EPLL), showing its tendency to further improve denoising performance. the above methods, instead of  ...  The convergence of this process is studied for the K-SVD image denoising and related algorithms.  ...  SOS boosting with state-of-the-art algorithms. The proposed SOS boosting is applicable to a wide range of denoising algorithms.  ... 
doi:10.1137/140990978 fatcat:3krsdfs7pbam5lnmhglpajaqzm

A Boosting Procedure for Variational-Based Image Restoration

Samad Wali
2018 Numerical Mathematics: Theory, Methods and Applications  
Variational methods are an important class of methods for general image restoration. Boosting technique has been shown capable of improving many image denoising algorithms.  ...  The convergence analysis of the boosting process is shown in a special case of total variation image denoising with a "disk" input data.  ...  Table 1 : 1 Comparison between the image denoising results (SNR in dB) of TV and TGV algorithms and their boosting outcomes. σ Image λ 0 ρ τ TV TV-Boost TGV TGV-Boost 10 Man 23.23 0.1 1.3  ... 
doi:10.4208/nmtma.oa-2017-0046 fatcat:54jqqxjygvh4tn4htzqfmipvqy

Deep Boosting for Image Denoising [chapter]

Chang Chen, Zhiwei Xiong, Xinmei Tian, Feng Wu
2018 Lecture Notes in Computer Science  
In the scenario of image denoising, however, the existing boosting algorithms are surpassed by the emerging learning-based models.  ...  Boosting is a classic algorithm which has been successfully applied to diverse computer vision tasks.  ...  In this paper, we embed the deep learning technique into the boosting algorithm and significantly boost its performance in the scenario of image denoising.  ... 
doi:10.1007/978-3-030-01252-6_1 fatcat:twmraeryojfr3jcse6yqfcsmmq

A New Boosting Algorithm for Shrinkage Curve Learning

Xiyan Meng, Fang Zhuang, Francesco Lolli
2022 Mathematical Problems in Engineering  
To a large extent, classical boosting denoising algorithms can improve denoising performance. However, these algorithms can only work well when the denoisers are linear.  ...  In this paper, we propose a boosting algorithm that can be used for a nonlinear denoiser.  ...  Acknowledgments is study was supported by the National Natural Science Foundation of China (Grant nos. 61763009, 61761030, and 62061016), the Doctoral Scientific Fund Project of Hubei Minzu University  ... 
doi:10.1155/2022/6339758 fatcat:bvyjguqpfrdrhidahx6ybriqw4

Fast and Adaptive Boosting Techniques for Variational Based Image Restoration

Samad Wali, Chunming Li, Abdul Basit, Abdul Shakoor, Raheel Ahmed Memon, Sabit Rahim, Samina Samina
2019 IEEE Access  
Boosting techniques have been shown capable of improving many image restoration algorithms. This paper considers four fast and adaptive boosting techniques for variational based image restoration.  ...  The adaptive boosting frameworks can compute the existing image restoration algorithm iteratively.  ...  In spite of the great success of the above methods and algorithms, the quality of an image can be improved during restoration by using boosting techniques.  ... 
doi:10.1109/access.2019.2959003 fatcat:73fdctz3tvdepo6rrxdhgb4yii

Image and Spectrum Image Denoising under the local low Rank Assumption

Jakob Spiegelberg, Juan Carlos Idrobo, Jan Rusz
2018 Microscopy and Microanalysis  
The three principal denoising strategies used in state of the art algorithms are the exploitation of (self-)similarity by averaging similar signals (e.g., averaging of two consecutively measured images  ...  LLR performs competitively for denoising of both spectrum images and STEM images.  ...  The three principal denoising strategies used in state of the art algorithms are the exploitation of (self-)similarity by averaging similar signals (e.g., averaging of two consecutively measured images  ... 
doi:10.1017/s1431927618003380 fatcat:5mfydtqx3ba4hhp5gk3hy6fj4i

Improving K-SVD denoising by post-processing its method-noise

Yaniv Romano, Michael Elad
2013 2013 IEEE International Conference on Image Processing  
Various patch-based image denoising algorithms have been shown to be very effective.  ...  Nevertheless, in most cases the difference between the noisy image and its denoised version (called "method-noise") still contains traces of the original image content.  ...  leave more image-content.  ... 
doi:10.1109/icip.2013.6738090 dblp:conf/icip/RomanoE13 fatcat:hhuacsodzbdidlrhgujabg4z7y

Implementation of a Denoising Algorithm Based on High-Order Singular Value Decomposition of Tensors

Fabien Feschet
2019 Image Processing On Line  
This article presents an implementation of a denoising algorithm based on High-Order Singular Value Decomposition (HOSVD) of tensors.  ...  As it is common in patch-based algorithms, all tensors containing a pixel are then merged to produce an output image.  ...  We thank Pablo Arias and Jean-Michel Morel for providing us specific code for avoiding quantization when saving noisy images.  ... 
doi:10.5201/ipol.2019.226 fatcat:3pvpyx5f5jgkteanb27plck34q

Performance Analysis of Weighted Encoding with Sparse Nonlocal Regularization and Spatially Adaptive Iterative Filtering Boost Denoising: A Review
english

Shivam Shukla, Vijayshri Chaurasia
2015 International Journal of Scientific Engineering and Technology  
These approaches has ability of filtering local image content iteratively using the given base filter, and the type of iteration and the iteration number are automatically optimized with respect to estimated  ...  In this paper, we compare the spatially adaptive iterative filtering (SAIF) approach with Weighted Encoding with Sparse Nonlocal Regularization (WESNR) to maintain the denoising strength locally for any  ...  The so-called LPG-PCA algorithm provides very good edge preservation performance.  ... 
doi:10.17950/ijset/v4s8/810 fatcat:kcvsutlenzda7c2o6wrki56nxe

Optimal Combination of Image Denoisers [article]

Joon Hee Choi, Omar Elgendy, Stanley H. Chan
2019 arXiv   pre-print
; (2) A deep neural network to estimate the mean squared error (MSE) of denoised images without needing the ground truths; (3) An image boosting procedure using a deep neural network to improve contrast  ...  Given a set of image denoisers, each having a different denoising capability, is there a provably optimal way of combining these denoisers to produce an overall better result?  ...  (See additional discussion for the image denoising problem in [55] .) In the image denoising literature, the above idea of boosting has been studied in multiple places such as [54] - [56] .  ... 
arXiv:1711.06712v4 fatcat:oftvkqovivalvpvknm4jurd6ua

Synergy Between Semantic Segmentation and Image Denoising via Alternate Boosting [article]

Shunxin Xu, Ke Sun, Dong Liu, Zhiwei Xiong, Zheng-Jun Zha
2021 arXiv   pre-print
We observe that not only denoising helps combat the drop of segmentation accuracy due to noise, but also pixel-wise semantic information boosts the capability of denoising.  ...  The capability of image semantic segmentation may be deteriorated due to noisy input image, where image denoising prior to segmentation helps.  ...  Boosting, an algorithm for improving the performance of various tasks by cascading the same models, has been adopted in image denoising not only in the traditional way [4, 30] but also with CNN-based  ... 
arXiv:2102.12095v1 fatcat:fbnz55d24ncydod7yaclmrm7sm

A Critical Analysis of Patch Similarity Based Image Denoising Algorithms [article]

Varuna De Silva
2020 arXiv   pre-print
Most of the algorithms for image denoising has focused on the paradigm of non-local similarity, where image blocks in the neighborhood that are similar, are collected to build a basis for reconstruction  ...  Through rigorous experimentation, this paper reviews multiple aspects of image denoising algorithm development based on non-local similarity.  ...  Finally, most of the algorithms use a boosting technique to improve an initial denoised estimate.  ... 
arXiv:2008.10824v1 fatcat:fblahbzbvng7tdokhfpfoe7kfa

A New Faster, Better Pixels Weighted Don't Care Filter for Image Denoising and Deblurring

Rachana Dhannawat
2020 International Journal of Advanced Trends in Computer Science and Engineering  
This filter is used for image deblurring as well and the results are improved in terms of PSNR and SSIM by 11% and 1 % respectively.  ...  As this filter has improved results for denoising as well as deblurring, it is called as a dual purpose filter. The filter is tested for both gray and colour images and improves results for both.  ...  For color images, we work with only 3*3 sizes. High boost filter results are not promising for denoising so not considered for further extended dimensions.  ... 
doi:10.30534/ijatcse/2020/212922020 fatcat:77yuepzemze3hprwop3magx6o4
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