Underwater Image Enhancement Using SWT Based Image Fusion and Colour Correction

Bhagyasri, G; Prasannakumar, G.; Murthy, P. S. N.

doi:10.1109/iccs45141.2019.9065524

Cited by 8 publications

(3 citation statements)

References 25 publications

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“…The Dark Channel Prior (DCP) technique is frequently used to get a haze free image. On the other hand, this method is utilized to improve underwater images (Bhagyasri et al, 2019).…”

Section: Color Correction Algorithmmentioning

confidence: 99%

Underwater Fused Image Classification Using Deep Learning Based Resnet and Hybrid PSO + HHO Model

Sarath¹,

Sucharitha²

2023

Journal of Computer Science

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In image fusion, multiple images are combined into one with minimal distortion and data loss. Image fusion forms a highly configured image with good results. The image fusion technique is employed in various domains, including remote sensing, robotics, medical applications, and underwater image processing. The focus of this study is on a unique underwater image fusion approach that allows for greater flexibility in the construction of fusion criteria. The characteristics of the input images are extracted using a Modified Tetrolet Transform (MMT), which may be employed together or independently. Our aim is to apply image deep learning algorithms such as GoogleNet, AlexNet, and ResNet for fusion to the original image and optimized algorithm PSO and HHO to be used for optimizing the fused image. Finally, the images are classified as good quality images and poor-quality images. The ResNet with hybrid HHO and PSO method has high efficiency in image fusion, according to numerical data the proposed model with good quality attains accuracy, sensitivity, specificity, precision, and F1-measure are 96.32, 94.25, 95.73, 98.34, and 95.55. in addition, the poor-quality images attain accuracy, sensitivity, specificity, precision, and F1-measure are 96.22, 94.15, 95.63, 98.24, and 95.45 This method optimizes the exposure of the dark areas, increases contrast, and preserves and enhances the edges. Our image trial findings show that this technique substantially improves the underwater image quality.

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“…The Dark Channel Prior (DCP) technique is frequently used to get a haze free image. On the other hand, this method is utilized to improve underwater images (Bhagyasri et al, 2019).…”

Section: Color Correction Algorithmmentioning

confidence: 99%

Underwater Fused Image Classification Using Deep Learning Based Resnet and Hybrid PSO + HHO Model

Sarath¹,

Sucharitha²

2023

Journal of Computer Science

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show abstract

“…The visibility restoration of an underwater image improves the visual distance in a scene, which is conducive to underwater rescue and surveys. Studies on underwater image visibility restoration conducted in the past can be categorized into three types, namely (a) improved dark channel prior methods [1][2][3][4][5][6][7][8][9], (b) fusion-based methods [10][11][12][13][14], and (c) deep learning based methods [15][16][17][18]. The underwater image visibility restoration method based on deep learning requires synthetic datasets, which do not contain realistic (practical) information, and usually lead to model over-fitting.…”

Section: Introductionmentioning

confidence: 99%

“…To summarize, in order to recover a clean image (with clear scene visibility) from a degraded underwater image (i.e., image captured underwater by a camera), different methods can be used [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18], amongst which the improved dark channel method based on physical model is often used. There are many types of underwater image restoration methods based on improved dark channel prior, and the most commonly used method is the red-channel underwater restoration method.…”

Section: Introductionmentioning

confidence: 99%