Comparison Of Some Speckle Reduction Techniques For Sar Images

Dewaele, Piet; Wambacq, Patrick; Oosterlinck, André; Marchand, Jean

doi:10.1109/igarss.1990.689028

Cited by 25 publications

(15 citation statements)

References 9 publications

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“…total of 20 possible values of speckle noise was used. Performance of all the schemes have been qualitatively evaluated in terms of mean-square-error (MSE) [23], normalized mean-square-error (NMSE) [23], peak signal-to-noise ratio (PSNR) [23], speckle index [25], average signal-to-noise ratio (SNR) [25], effective number of looks (ENL) [23], correlation parameter (CP) [23], mean structure similarity index map (MSSIM) [24] and execution time in seconds. The correlation parameter is a measure of edge preservation in reconstructed speckle reduced image and MSSIM is a measure for comparing luminance, contrast and structure of two different images.…”

Section: Experimental Results and Performance Analysismentioning

confidence: 99%

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Comparison of PDE based and other techniques for speckle reduction from digitally reconstructed holographic images

Srivastava

Gupta

Parthasarthy

2010

Optics and Lasers in Engineering

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Section: Experimental Results and Performance Analysismentioning

confidence: 99%

“…Speckle index [25]: Since speckle noise is multiplicative in nature, average contrast of an image may be treated as a measure of speckle removal. Speckle index (SI) is defined as…”

Section: Performance Measurement Metricsmentioning

confidence: 99%

Comparison of PDE based and other techniques for speckle reduction from digitally reconstructed holographic images

Srivastava

Gupta

Parthasarthy

2010

Optics and Lasers in Engineering

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“…The parameters Speckle Index (SI), Equivalent Number of Looks (ENL) and Speckle Suppression Index (SSI) are used to evaluate the denoising effect. SI of the reconstructed image is [11] …”

Section: Optical Way To Suppress Specklementioning

confidence: 99%

Two-stage method to suppress speckle noise in digital holography

Leng

Zhou

Lang

et al. 2015

Opt Rev

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The two-stage method is proposed to suppress speckle noise in the digital hologram. Three kinds of optical denoising ways are analyzed and compared at first. The optimal one is used to reduce speckle preliminarily. At the same time, the statistical property of the speckle is changed by the optical way. Then the optimized NLM algorithm is adopted to further suppress speckle noise. The experimental system is set up, and the performance indices are calculated. The results are compared with other algorithms. It is demonstrated that the presented method can effectively suppress speckle noise in the digital hologram and the processed image is very vivid.

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“…Image smoothing can then be obtained in designated scales. Mastin (1985) and Dewaele et al (1990) have evaluated various noise-smoothing techniques, including mean, median, K-NN, gradient-inverse , Lee's additive, Lee's multiplicative, sigma and geometric lters. Huang and Van Genderen (1996) systematically reviewed and evaluated a wide range of ltering techniques for SAR speckle reduction.…”

Section: Experimental Datamentioning

confidence: 99%