A generalization of morphological filters using multiple structuring elements

Song, Jisheng; Delp, Edward J.

doi:10.1109/iscas.1989.100518

Cited by 18 publications

(5 citation statements)

References 12 publications

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“…Although the experiments were perfonned on color images, only luminance images are shown in the figures, due to printing constraints. The grayscale morphological filter used for all of these experiments was the 2DCO filter introduced by Stevenson and Arce [9,10] and extended by Song and Deip [11,12,13].…”

Section: Resultsmentioning

confidence: 99%

<title>Empirical study of morphological operators in color image enhancement</title>

Comer

Delp

1992

SPIE Proceedings

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The use of mathematical morphology in low and mid-level image processing and computer vision applications has allowed the development of a class of techniques for analyzing shape information in monochromatic images. In this paper, we extend some of these techniques to color images. We have investigated the application of various methods for "color morphology". We present results of our empirical study for three different applications: noise suppression, multiscale smoothing, and edge detection.

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Section: Resultsmentioning

confidence: 99%

<title>Empirical study of morphological operators in color image enhancement</title>

Comer

Delp

1992

SPIE Proceedings

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“…According to the mutual spatial relationship of image pixels, Song [10] offered a morphology filter model of multiple structuring elements with different direction properties. The model defines four kinds of lineal structures in the direction of 0u, 45u, 90u and 135u.…”

Section: Feature Similarity Calculationmentioning

confidence: 99%

Image content authentication technique based on Laplacian Pyramid

Wan

Han

2008

Front. Electr. Electron. Eng. Ch

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This paper proposes a technique of image content authentication based on the Laplacian Pyramid to verify the authenticity of image content. First, the image is decomposed into Laplacian Pyramid before the transformation. Next, the smooth and detail properties of the original image are analyzed according to the Laplacian Pyramid, and the properties are classified and encoded to get the corresponding characteristic values. Then, the signature derived from the encrypted characteristic values is embedded in the original image as a watermark. After the reception, the characteristic values of the received image are compared with the watermark drawn out from the image. The algorithm automatically identifies whether the content is tampered by means of morphologic filtration. The information of tampered location is p resented at the same time. Experimental results show that the proposed authentication algorithm can effectively detect the event and location when the original image content is tampered. Moreover, it can tolerate some distortions produced by compression, filtration and noise degradation.

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“…Given the model of data acquisition, the conditional distribution is related to the noise distribution by Pr(y [ z) = Pr(n)ln=y_z (8) Thus it is necessary to develop accurate statistical models for the noise Pr(n) and for the signal Pr(z). The i.i.d.…”

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confidence: 99%

Nonlinear filtering structure for image smoothing in mixed-noise environments

Stevenson

Schweizer

1992

J Math Imaging Vis

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This paper introduces a new nonlinear filtering structure for filtering image data that have been corrupted by both impulsive and nonimpulsive additive noise. Like other nonlinear filters, the proposed filtering structure uses order-statistic operations to remove the effects of the impulsive noise. Unlike other filters, however, nonimpulsive noise is smoothed by using a maximum a posterior/ estimation criterion. The prior model for the image is a novel Markov random-field model that models image edges so that they are accurately estimated while additive Gaussian noise is smoothed. The Markov random-field-based prior is chosen such that the filter has desirable analytical and computational properties. The estimate of the signal value is obtained at the unique minimum of the a posterior/log likelihood function. This function is convex so that the output of the filter can be easily computed by using either digital or analog computational methods. The effects of the various parameters of the model will be discussed, and the choice of the predetection order statistic filter will also be examined. Example outputs under various noise conditions will be given.

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A generalization of morphological filters using multiple structuring elements

Cited by 18 publications

References 12 publications

<title>Empirical study of morphological operators in color image enhancement</title>

<title>Empirical study of morphological operators in color image enhancement</title>

Image content authentication technique based on Laplacian Pyramid

Nonlinear filtering structure for image smoothing in mixed-noise environments

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