The analysis of morphological filters with multiple structuring elements

Song, Jisheng; Delp, Edward J.

doi:10.1016/0734-189x(90)90150-t

Cited by 95 publications

(22 citation statements)

References 6 publications

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“…Such a modification was presented by Song and Delp (1990), and Cheng and Venetsanopoulos (1992), and it uses a combination of multiple images obtained with a single SE, together composing a multiple SE. This kind of filter may be edge preserving (Cheng and Venetsanopoulos, 1992;Kupidura, 2006;Kupidura, Jakubiak, 2009) or area preserving (Vincent, 1993), depending on the set of the structuring elements.…”

Section: Morphological Alternate Filtersmentioning

confidence: 99%

Comparison of Filters Dedicated to Speckle Suppression in Sar Images

Kupidura¹

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:This paper presents the results of research on the effectiveness of different filtering methods dedicated to speckle suppression in SAR images. The tests were performed on RadarSat-2 images and on an artificial image treated with simulated speckle noise. The research analysed the performance of particular filters related to the effectiveness of speckle suppression and to the ability to preserve image details and edges. Speckle is a phenomenon inherent to radar images -a deterministic noise connected with land cover type, but also causing significant changes in digital numbers of pixels. As a result, it may affect interpretation, classification and other processes concerning radar images. Speckle, resembling "salt and pepper" noise, has the form of a set of relatively small groups of pixels of values markedly different from values of other pixels representing the same type of land cover. Suppression of this noise may also cause suppression of small image details, therefore the ability to preserve the important parts of an image, was analysed as well. In the present study, selected filters were tested, and methods dedicated particularly to speckle noise suppression: Frost, Gamma-MAP, Lee, Lee-Sigma, Local Region, general filtering methods which might be effective in this respect: Mean, Median, in addition to morphological filters (alternate sequential filters with multiple structuring element and by reconstruction). The analysis presented in this paper compared the effectiveness of different filtering methods. It proved that some of the dedicated radar filters are efficient tools for speckle suppression, but also demonstrated a significant efficiency of the morphological approach, especially its ability to preserve image details.

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Section: Morphological Alternate Filtersmentioning

confidence: 99%

Comparison of Filters Dedicated to Speckle Suppression in Sar Images

Kupidura¹

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…The last kind of operation to be presented in this section is an operation with multiple SE (Stevenson & Arce 1987;Song & Delp 1990;Cheng & Venetsanopoulos 1992;Vincent 1992Vincent , 1993. Actually it is not a separate operation, but rather a modification, which may be used for most morphological operations.…”

Section: Theorymentioning

confidence: 99%

CMAF – CHRIS Morphological Adaptive Filter

Kupidura

2013

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Abstract. The paper presents a new method of CHRIS images filtering. The presented algorithm is based on mathematical morphology operations and allows to correct the main CHRIS images noise types, like missing pixels and vertical stripes caused by a malfunctioning of the device. the algorithm is preceded by the brief discussion on the nature of the noise and the basis of mathematical morphology. The resulting images are compared to the results of application of other types of CHRIS-dedicated algorithms (Settle methods).

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“…Various interactions of the original set with the structuring element form the basis of all morphological operations. 17 There are four basic morphological operators: erosion, dilation, opening, and closing. In our paper, the opening and closing operations are used to extract noise from an original image.…”

Section: Noise Filteringmentioning

confidence: 99%

Length estimation of digit strings using a neural network with structure-based features

Chi²,

Siu

1998

J. Electron. Imaging

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Abstract. Accurate length estimation is very helpful for the successful segmentation and recognition of connected digit strings, in particular, for an off-line recognition system. However, little work has been done in this area due to the difficulties involved. A length estimation approach is presented as a part of our automatic off-line digit recognition system. The kernel of our approach is a neural network estimator with a set of structure-based features as the inputs. The system outputs are a set of fuzzy membership grades reflecting the degrees of an input digit string of having different lengths. Experimental results on National Institute of Standards and Technology (NIST) Special Database 3 and other derived digit strings shows that our approach can achieve an about 99.4% correct estimation if the best two estimations are considered. © 1998 SPIE and IS&T. [S1017-9909(98)

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The analysis of morphological filters with multiple structuring elements

Cited by 95 publications

References 6 publications

Comparison of Filters Dedicated to Speckle Suppression in Sar Images

Comparison of Filters Dedicated to Speckle Suppression in Sar Images

CMAF – CHRIS Morphological Adaptive Filter

Length estimation of digit strings using a neural network with structure-based features

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