Neutrosophic data formation using Gaussian filter based costas coding for wireless communication systems

Ajith, A.S.; Latha, T.

doi:10.1016/j.cogsys.2018.09.030

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…e dark channel priority law considers that most of the fog-free outdoor natural scene images are processed by the dark channel priority. e brightness of the pixels will be close to zero, and if there are a large number of bright pixels in the dark channel image, this brightness should come from the fog in the air or the sky [19,20]. For the fogged original image, the initial transmission map x i (t) and air color value C(t) will be able to be obtained from the result of the dark channel prioritization.…”

Section: Local Dehazing Of Single Image Based On Dark Channelmentioning

confidence: 99%

Local Defogging Algorithm for Improving Visual Impact in Image Based on Multiobjective Optimization

Qiu-ju

2022

Mathematical Problems in Engineering

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The preprocessing of images is required for many applications based on industry, social, and academic requirements. Researchers have developed a number of techniques to improve the visual effect of images and appropriately interpret visual effects. The accuracy of visuals is important in cyber security, military organization, police organizations, and forensics to detect the true story from the pictures. They search for evidence by digging deep into the network in search of evidence. If visuals are not clear, preprocessing of images is not done correctly, then it may lead to wrong interpretations. This paper proposes an image local defogging technique based on multiobjective optimization to improve the visual effect of the image as well as the information entropy. The multiobjective function is selected to establish the image reconstruction model based on multiple objectives. The model is utilized to reconstruct a single image to moderate the impact of noise and other interference factors in the original image. The color constancy model and effective detail intensity model are also devised for image enhancement to get the visual details. The atmospheric light value and transmittance are evaluated using a physical model of atmospheric scattering, and the guided filter is used to maximize the transmittance of a single image and improve the efficiency of image defogging. The dark channel priority method is used to realize the local defogging of a single image and to design the local defogging algorithm. Experiments verify the optimization effect of the proposed algorithm in terms of information entropy and container network interface (CNI) value. The tone restoration degree is good, and it improves the overall image quality. The image defogging effect of the proposed algorithm is verified with respect to subjective and objective levels to check the efficacy of the proposed multiobjective model.

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Section: Local Dehazing Of Single Image Based On Dark Channelmentioning

confidence: 99%

Local Defogging Algorithm for Improving Visual Impact in Image Based on Multiobjective Optimization

Qiu-ju

2022

Mathematical Problems in Engineering

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Difference of Gaussian Convolutional Sparse Principal Component Thermography for Defect Signal Enhance in Composite Materials

Liu

Zhang

et al. 2021

2021 3rd International Conference on Industrial Artificial Intelligence (IAI)

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Visual retrieval of digital media image features based on active noise control

Zhang¹

2022

JCM

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In order to improve the recall and precision of image retrieval, a visual retrieval method of digital media image features based on active noise is proposed. In this paper, Canny algorithm is used to detect the edge of the image to get the feature information of the edge of the image. The RGB color space model is used to decompose the color information of the image, and the color characteristic information of the image is obtained. Extracting image features to retain the useful information contained in the image as much as possible; In order to facilitate the visual retrieval of image features, reduce the retrieval complexity and further fuse image features, FPCA and ReliefF algorithms are used to reduce the dimensionality of image features, and the active noise control method is used to sharpen the image. After processing the results, a digital media image feature visual retrieval platform is established to realize the visual retrieval of digital media image features. Experimental results show that the proposed method has a high accuracy of over 80% and a high recall rate of 95.2%.

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Neutrosophic data formation using Gaussian filter based costas coding for wireless communication systems

Cited by 3 publications

References 12 publications

Local Defogging Algorithm for Improving Visual Impact in Image Based on Multiobjective Optimization

Local Defogging Algorithm for Improving Visual Impact in Image Based on Multiobjective Optimization

Difference of Gaussian Convolutional Sparse Principal Component Thermography for Defect Signal Enhance in Composite Materials

Visual retrieval of digital media image features based on active noise control

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