Speckle Reduction by Directional Coherent Anisotropic Diffusion

Zhang, Guo; Feng, Guo; Zhang, Qingjun; Kai, Xu; Jia, Peng; Hao, Xiaoyan

doi:10.3390/rs11232768

Cited by 9 publications

(4 citation statements)

References 31 publications

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“…The application of ENL as the main index for evaluating noise attenuation capacity in homogeneous areas in SAR images (Zhang et al 2019) showed that the smoothing capacity is influenced by the type of filter, polarization, window size, and vigor condition of the Caatinga. It was common to observe the high standard deviations among all the answers found, which hindered the statistical discrimination between the compared means.…”

Section: Discussionmentioning

confidence: 99%

Speckle reduction for Sentinel-1A SAR images in the Semi-arid caatinga region, Brazil

Jesus,

Kuplich,

Barreto

et al. 2023

Bol. Ciênc. Geod.

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Due to the absence of studies related to the digital processing of synthetic aperture radar (SAR) images in the semi-arid region of Brazil, the aim of this study was to test different filters for reducing speckle noise in SAR images, serving as a reference for choosing the most suitable filter for different studies in this vegetation. The filters: Gamma Map, Lee Sigma, Median, Frost and Refined Lee in different window sizes were tested on the VV, VH and VH/VV polarizations in the Sentinel-1A images, verifying the responses under the influence of the dry and post-rainy period in the Caatinga vegetation. In the state of Sergipe, Brazil, 30 samples of Caatinga fragments obtained from Sentinel-1A images for the dry and post-rainy season were selected. For all images evaluated, the values of the averages of the equivalent number of looks (ENL) were compared by the Tukey test at 5% significance. The Gamma filter showed the highest amount of means ( 22) with the highest ENL values, followed by Median (5). The generation of ENL results and their comparison, considering all variables used, was essential to serve as a basis for choosing the filtering method in studies that use data from Sentinel-1A in the Caatinga region.

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Section: Discussionmentioning

confidence: 99%

Speckle reduction for Sentinel-1A SAR images in the Semi-arid caatinga region, Brazil

Jesus,

Kuplich,

Barreto

et al. 2023

Bol. Ciênc. Geod.

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show abstract

“…Objective evaluation is based on the use of quantitative indicators of the model to systematically measure the image quality without relying on subjective perceptions and is therefore more rational. Objective evaluation is currently the primary method used for image quality evaluation (Zhang et al, 2019). Here, signal-to-noise ratio (SNR), standard deviation (σ), equivalent number of looks (ENL), radiative resolution (RS), speckle noise index (SNI), and multi-temporal image filtering edge coefficient (MEC) were the evaluation parameters.…”

Section: Evaluation Methodsmentioning

confidence: 99%

“…These algorithms are simple and easy to implement; however, the filtering algorithm shows weak adaptability when dealing with SAR images with complex local geometry. Partial differential anisotropic diffusion filtering is represented by classical speckle reducing anisotropic diffusion (SRAD) and its improved algorithm (Zhang et al, 2019;Guo et al, 2022). This type of algorithm can be considered as an iterative Lee filter, which is an edge-sensitive diffusion filter and can well-maintain edge details in an image.…”

Section: Introductionmentioning

confidence: 99%

Multitemporal SAR image despeckling based on non-local theory

Wang

Deng

Wang

et al. 2023

Front. Environ. Sci.

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In this paper, a multitemporal SAR image despeckling based on non-local theory (NLG-MulSAR) algorithm is proposed, which is improved based on the basic framework of the ratio-based multitemporal SAR image denoising (RABASAR). The temporal and spatial information of a multitemporal SAR image is integrated. The super image and the ratio image acquisition part of the RABASAR algorithm are optimized by the NLG filtering algorithm. The NLG algorithm does not need to transform multiplicative noise into additive noise on a synthetic aperture radar (SAR) image and then filter it. The NLG algorithm uses the nonlinear method to eliminate the influence of strong noise points while preserving image edge features. Based on the number of pixels in the non-local image block, the NLG algorithm avoids the generation of fuzzy noise on the filtered image. In this study, we use seven Gaofen three SAR images captured at different times in the Beijing area as experimental data to evaluate the effect of filtering methods in terms of five objective parameters: signal-to-noise ratio, standard deviation, equivalent number of looks, radiative resolution, and speckle noise index. In addition, based on the ratio image, we propose an index, namely the filtering edge coefficient of a multitemporal SAR image, to evaluate the filtering edge retention characteristics of a multitemporal SAR image. The results show that compared with the RABASAR filtering algorithm, the proposed NLG-MulSAR filtering algorithm can better balance the relationship between multiplicative noise and texture detail information and attenuate the speckle while protecting the texture detail information on the SAR image.

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“…Image retrieval approach that applies locality-sensitive hashing with convolutional neural networks to extract several feature types. This approach concentrates on both the high-level and low-level, which offers visual content of the images [12]. The artificial neural network is utilized to precisely notice the mass lesions in the mammogram images in a short time [13].…”

Section: Related Workmentioning

confidence: 99%

An underwater image enhancement by reducing speckle noise using modified anisotropic diffusion filter

Malathi,

Manikandan

2023

IJECE

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Underwater images are usually suffering from the issues of quality degradation, such as low contrast due to blurring details, color deviations, non-uniform lighting, and noise. Since last few decades, many researches are undergoing for restoration and enhancement for degraded underwater images. In this paper, we proposed a novel algorithm using modified anisotropic diffusion filter with dynamic color balancing strategy. This proposed algorithm performs based on an employing effective noise reduction as well as edge preserving technique with dynamic color correction to make uniform lighting and minimize the speckle noise. Furthermore, reanalyze the contributions and limitations of existing underwater image restoration and enhancement methods. Finally, in this research provided the detailed objective evaluations and compared with the various underwater scenarios for above said challenges also made subjective studies, which shows that our proposed method will improve the quality of the image and significantly enhanced the image.

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Speckle Reduction by Directional Coherent Anisotropic Diffusion

Cited by 9 publications

References 31 publications

Speckle reduction for Sentinel-1A SAR images in the Semi-arid caatinga region, Brazil

Speckle reduction for Sentinel-1A SAR images in the Semi-arid caatinga region, Brazil

Multitemporal SAR image despeckling based on non-local theory

An underwater image enhancement by reducing speckle noise using modified anisotropic diffusion filter

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