Investigation of methods to search for the boundaries on the image and their use on lung hardware of methods finding saliency map

Semenishchev, Evgeny A.; Marchuk, Vladimir; Fedosov, V. P.; Stradanchenko, Sergey; Ruslyakov, Dmitriy

doi:10.1117/12.2176950

Cited by 13 publications

(7 citation statements)

References 8 publications

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“…In the second case: b.1) We make an exception the background image from consideration. As a method for determining the background can be used the approaches based on the analysis of the boundaries of objects and their mutual arrangement [9]. It is also possible to use trained neural network, a threshold method and methods based on human saliency map.…”

Section: Image Denoising Methods Using a Combined Criterionmentioning

confidence: 99%

The algorithm stitching for medical imaging

et al. 2016

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In this paper we propose a stitching algorithm of medical images into one. The algorithm is designed to stitching the medical x-ray imaging, biological particles in microscopic images, medical microscopic images and other. Such image can improve the diagnosis accuracy and quality for minimally invasive studies (e.g., laparoscopy, ophthalmology and other). The proposed algorithm is based on the following steps: the searching and selection areas with overlap boundaries; the keypoint and feature detection; the preliminary stitching images and transformation to reduce the visible distortion; the search a single unified borders in overlap area; brightness, contrast and white balance converting; the superimposition into a one image. Experimental results demonstrate the effectiveness of the proposed method in the task of image stitching.

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Section: Image Denoising Methods Using a Combined Criterionmentioning

confidence: 99%

The algorithm stitching for medical imaging

et al. 2016

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“…The analyzer is built on the basis of calculating the weighted value of the number of color gradient transitions per unit area. The stage of searching for areas with a large number of highly detailed elements on a simple background or simple elements on a highly detailed background is performed using the approach described in [16]. The main stages of the operation are:…”

Section: 42mentioning

confidence: 99%

Pre-processing and data fusion of a complex image obtained by a pair of sensors with a free arrangement

Semenishchev

Voronin

Zelensky

et al. 2023

Optoelectronic Imaging and Multimedia Technology IX

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The article an approach to improve the accuracy of restoring the boundaries of objects obtained to create 3D structures by The paper proposes a data processing algorithm that allows performing primary processing operations in order to identify the main parameters and fusion them into a single image. To form a complex image, it is possible to first enter the parameters selected by the operator, which corrects the mixing ratio. As a noise reduction algorithm for different ranges, the multi-criteria filtering method is used, which is based on minimizing the sum of the squared deviations of the input signal and the generated estimate, as well as the sum of the squared differences of the obtained estimates. Using the adjustment factor allows you to set the degree of influence of the criterion on the resulting processing. Using this method also allows you to detect the boundaries of objects. The search for the border is based on the analysis of frequency components and the search for sharp changes in color gradation. The possibility of applying this approach for various types of data is shown on the example of processing parallel streams. For the primary construction of areas of significance, an algorithm for changing the range of clusters and an object complexity analyzer are used. The analyzer is built on the basis of calculating the weighted value of the number of color gradient transitions per unit area. To visually improve the quality of the data, a color space conversion algorithm based on alpha mixed is used. As test data used to evaluate the effectiveness, pairs of test images are used, obtained by sensors fixed at resolution of 1024x768 (8 bit, color image) and far-IR spectrum 320x240 (8 bit, color image). Images of simple shapes are used as analyzed objects.

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“…Image analysis to identify areas with a large number of boundaries. To do this, we use the method described in [14].…”

Section: Base Algorithm For Improving the Quality And Visibility Of O...mentioning

confidence: 99%

Improving the quality and visibility of objects in images captured in difficult weather conditions

Semenishchev

Zelensky²,

Ilyukhin³

et al. 2022

Environmental Effects on Light Propagation and Adaptive Systems V

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The article proposes an approach to improve the visual quality of generated images based on the use of primary data processing methods. To reduce the effect of noise associated with the appearance of dust or water droplets, a multi-criteria filtering method is proposed for use. The proposed method allows two-pass processing. At the first stage, the method uses a criterion that forming strong noise suppression with blurring of the boundaries. Based on the generated data, we perform filtering while preserving and strengthening the boundaries of objects. Next, we perform the formation of a combined approach to fusion of image. In the case of low illumination, the noise component is strong and its suppression is an important problem. In the case of fog, the task is complicated, since the boundaries of objects are blurred. An adaptive non-linear alpha-contrasting algorithm is used for elimination and compensation. Pairs of test images obtained by sensors with a resolution of 6000x4000 (8 bit, color image, visible range) are used as test data used to evaluate the effectiveness, pairs of images with the same illumination but different fog density are used for the test. Images of simple shapes are used as analyzed objects.

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Investigation of methods to search for the boundaries on the image and their use on lung hardware of methods finding saliency map

Cited by 13 publications

References 8 publications

The algorithm stitching for medical imaging

The algorithm stitching for medical imaging

Pre-processing and data fusion of a complex image obtained by a pair of sensors with a free arrangement

Improving the quality and visibility of objects in images captured in difficult weather conditions

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