Speckle reduction with adaptive stack filters

Buemi, María Elena; Frery, Alejandro C.; Ramos, Heitor S.

doi:10.1016/j.patrec.2013.06.005

Cited by 11 publications

(6 citation statements)

References 19 publications

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“…Median filter is quite popular for nonlinear filtering in image processing applications [36] because it is simple and can preserve edges. A variety of median filters, such as stack filters and adaptive stack filters [37]- [39], the mean absolute error (MAE) of stack filter [40], multilevel median and FIR-median hybrid filter [41], adaptive switching median filter [42], optimal weighted vector median [43], [44], generalized Gaussian median filter [45], and relaxed median filter [46] have been developed to treat these drawbacks of [20]- [22], [24]- [31]. Although median filter and its various methods [37]- [46] are useful as nonlinear filter for satellite image denoising and enhancement, yet they also have some drawbacks.…”

Section: Deblocking Artifactmentioning

confidence: 99%

Deblocking Artifact of Satellite Image Based on Adaptive Soft-Threshold Anisotropic Filter Using Wavelet

Risnandar

Aritsugi

2018

IEICE Trans. Inf. & Syst.

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SUMMARYNew deblocking artifact, or blocking artifact reduction, algorithms based on nonlinear adaptive soft-threshold anisotropic filter in wavelet are proposed. Our deblocking algorithm uses soft-threshold, adaptive wavelet direction, adaptive anisotropic filter, and estimation. The novelties of this paper are an adaptive soft-threshold for deblocking artifact and an optimal intersection of confidence intervals (OICI) method in deblocking artifact estimation. The soft-threshold values are adaptable to different thresholds of flat area, texture area, and blocking artifact. The OICI is a reconstruction technique of estimated deblocking artifact which improves acceptable quality level of estimated deblocking artifact and reduces execution time of deblocking artifact estimation compared to the other methods. Our adaptive OICI method outperforms other adaptive deblocking artifact methods. Our estimated deblocking artifact algorithms have up to 98% of MSE improvement, up to 89% of RMSE improvement, and up to 99% of MAE improvement. We also got up to 77.98% reduction of computational time of deblocking artifact estimations, compared to other methods. We have estimated shift and add algorithms by using Euler + +(E + +) and Runge-Kutta of order 4++ (RK4 + +) algorithms which iterate one step an ordinary differential equation integration method. Experimental results showed that our E + + and RK4 + + algorithms could reduce computational time in terms of shift and add, and RK4 + + algorithm is superior to E + + algorithm.

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Section: Deblocking Artifactmentioning

confidence: 99%

Deblocking Artifact of Satellite Image Based on Adaptive Soft-Threshold Anisotropic Filter Using Wavelet

Risnandar

Aritsugi

2018

IEICE Trans. Inf. & Syst.

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“…Some image regularizing objectives that do not pertain to the PLS class are stack filters [29][30][31]. Stack filters include the classes of weighted medians and some morphological type filters.…”

Section: E-mail Addressesmentioning

confidence: 99%

“…The optimal solution for these stacked objectives is then determined as the solution of a linear program (see [31] for details). This optimal solution is mainly relevant for denoising purposes, see [29][30][31], among other references.…”

Section: E-mail Addressesmentioning

confidence: 99%

High order structural image decomposition by using non-linear and non-convex regularizing objectives

Atto¹,

Mercier

2015

Computer Vision and Image Understanding

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International audienceThe paper addresses structural decomposition of images by using a family of non-linear and non-convex objective functions. These functions rely on p quasi-norm estimation costs in a piecewise constant regularization framework. These objectives make image decomposition into constant cartoon levels and rich textural patterns possible. The paper shows that these regularizing objectives yield image texture-versus-cartoon decompositions that cannot be reached by using standard penalized least square regularizations associated with smooth and convex objectives

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“…(1) Speckle noise can be reduced by a stack filter [18], which is defined by the function S f : {0, 1,…,M} n ?…”

Section: Preprocessingmentioning

confidence: 99%

A novel ultrasound based approach for lesion segmentation and its applications in gynecological laparoscopic surgery

Gong

Liu

et al. 2015

Australas Phys Eng Sci Med

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Laparoscopic ultrasound (LUS) has been widely utilized as a surgical aide in general, urological, and gynecological applications. Our study summarizes the clinical applications of laparoscopic ultrasonography in laparoscopic gynecologic surgery. Retrospective analyses were performed on 42 women subjects using laparoscopic surgery during laparoscopic extirpation and excision of gynecological tumors in our hospital from August 2011 to August 2013. Specifically, the Esaote 7.5 × 10 MHz laparoscopic transducer was used to detect small residual lesions, as well as to assess, locate and guide in removing the lesions during laparoscopic operations. The findings of LUS were compared with those of preoperative trans-vaginal ultrasound, postoperative, and pathohistological examinations. In addition, a novel method for lesion segmentation was proposed in order to facilitate the laparoscopic gynecologic surgery. In our experiment, laparoscopic operation was performed using a higher frequency and more close to pelvic organs via laparoscopic access. LUS facilitates the ability of gynaecologists to find small residual lesions under laparoscopic visualization and their accurate diagnosis. LUS also helps to locate residual lesions precisely and provides guidance for the removal of residual tumor and eliminate its recurrence effectively. Our experiment provides a safer and more valuable assistance for clinical applications in laparoscopic gynecological surgery that are superior to trans-abdominal ultrasound and trans-vaginal ultrasound.

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Speckle reduction with adaptive stack filters

Cited by 11 publications

References 19 publications

Deblocking Artifact of Satellite Image Based on Adaptive Soft-Threshold Anisotropic Filter Using Wavelet

Deblocking Artifact of Satellite Image Based on Adaptive Soft-Threshold Anisotropic Filter Using Wavelet

High order structural image decomposition by using non-linear and non-convex regularizing objectives

A novel ultrasound based approach for lesion segmentation and its applications in gynecological laparoscopic surgery

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