mm-band radar image filtering with texture information preservation

Tsymbal, Oleg V.

doi:10.1109/msmw.2001.946879

Cited by 6 publications

(16 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The two latter ones are shown [10] to preserve texture well enough. The conclusions given in [10] coincide with the ones presented in our work [14], where the modified sigma filter [18] is also considered.…”

Section: Introductionsupporting

confidence: 85%

“…To name a few, we mention the papers of Yunhan et al [10], Aiazzi et al [12], as well as the book of Perry et al [13] (see also references therein). Preliminary results of the current paper have been published in [14,15]. The analysis here is more thorough and extended in many respects, one of the most important of which is additionally studied additive noise case.…”

Section: Introductionmentioning

confidence: 89%

“…In general, DPFs [16,17,18] preserve texture features not badly [10,14]. However, they are not the best choice for processing texture regions.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Three-State Locally Adaptive Texture Preserving Filter for Radar and Optical Image Processing

Tsymbal¹,

Ponomarenko

Zelensky

et al. 2005

EURASIP J. Adv. Signal Process.

View full text Add to dashboard Cite

Textural features are one of the most important types of useful information contained in images. In practice, these features are commonly masked by noise. Relatively little attention has been paid to texture preserving properties of noise attenuation methods. This stimulates solving the following tasks: (1) to analyze the texture preservation properties of various filters; and (2) to design image processing methods capable to preserve texture features well and to effectively reduce noise. This paper deals with examining texture feature preserving properties of different filters. The study is performed for a set of texture samples and different noise variances. The locally adaptive three-state schemes are proposed for which texture is considered as a particular class. For "detection" of texture regions, several classifiers are proposed and analyzed. As shown, an appropriate trade-off of the designed filter properties is provided. This is demonstrated quantitatively for artificial test images and is confirmed visually for real-life images.

show abstract

Section: Introductionsupporting

confidence: 85%

Section: Introductionmentioning

confidence: 89%

See 1 more Smart Citation

Three-State Locally Adaptive Texture Preserving Filter for Radar and Optical Image Processing

Tsymbal¹,

Ponomarenko

Zelensky

et al. 2005

EURASIP J. Adv. Signal Process.

View full text Add to dashboard Cite

show abstract

“…Because of this, this filter has been implemented in many software packages, for example, ENVI 3 ; and its basic application area is the processing of images formed by coherent imaging systems like synthetic aperture radars (SARs), medical ultrasound imagery, etc. 4 The Lee local statistic filter possesses such valuable properties as efficient noise suppression in image homogeneous regions, good edge, detail and texture preservation 5,6 , retaining mean level in image homogeneous regions even if multiplicative noise obeys non-Gaussian (Rayleigh, exponential or Gamma) distribution 7 . Its performance does not radically make worse if the multiplicative noise variance used as input parameter of Lee local statistic filter is determined (preestimated) with about 5-10% errors 8 .…”

Section: Introductionmentioning

confidence: 99%

“…However, there are two drawbacks of this class filters that appear themselves for the considered application. First, it is difficult to provide the desired trade-off of their properties; for example, better robustness to impulse noise commonly leads to worse suppression of multiplicative noise and poorer edge-detail-texture preservation 10,5 . Second, for probability density functions of multiplicative noise that are not symmetrical with respect to the unity mean (like Rayleigh or negative exponential pdfs of speckle) the application of order statistic filters often results in mean bias in image homogeneous regions 15,4 .…”

Section: Introductionmentioning

confidence: 99%

Robust Lee local statistic filter for removal of mixed multiplicative and impulse noise

2004

View full text Add to dashboard Cite

A robust version of Lee local statistic filter able to effectively suppress the mixed multiplicative and impulse noise in images is proposed. The performance of the proposed modification is studied for a set of test images, several values of multiplicative noise variance, Gaussian and Rayleigh probability density functions of speckle, and different characteristics of impulse noise. The advantages of the designed filter in comparison to the conventional Lee local statistic filter and some other filters able to cope with mixed multiplicative+impulse noise are demonstrated.

show abstract

Efficiency of DCT-Based Denoising Techniques Applied to Texture Images

Rubel¹,

Pogrebnyak

2014

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Textures or high-detailed structures contain information that can be exploited in pattern recognition and classification. If an acquired image is noisy, noise removal becomes an operation to improve image quality before further stages of processing. Among possible variants of denoising, we consider filters based on orthogonal transforms, in particular, on discrete cosine transform (DCT) known to be able to effectively remove additive white Gaussian noise (AWGN). Besides, we study a representative of nonlocal denoising techniques, namely, BM3D known as state-of-the-art technique based on DCT and similar patch search. We show that noise removal in texture images using the considered DCT-based techniques can distort fine texture details. To detect such situations and avoid texture degradation due to filtering, we propose to apply filtering efficiency prediction tests applicable to wide class of images. These tests are based on DCT coefficient statistic parameters and can be used for decision-making in relation to the use of the considered filters.

show abstract

mm-band radar image filtering with texture information preservation

Cited by 6 publications

References 0 publications

Three-State Locally Adaptive Texture Preserving Filter for Radar and Optical Image Processing

Three-State Locally Adaptive Texture Preserving Filter for Radar and Optical Image Processing

Robust Lee local statistic filter for removal of mixed multiplicative and impulse noise

Efficiency of DCT-Based Denoising Techniques Applied to Texture Images

Contact Info

Product

Resources

About