Underwater image enhancement using CLAHE in a reconfigurable platform

Alex, Raj S. M.; Deepa, S; Supriya, M. H.

doi:10.1109/oceans.2016.7761194

Cited by 13 publications

(4 citation statements)

References 3 publications

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“…The technique proposed by the authors aims to eliminate undesirable effects and restore clear visibility. Alex et al [19] showed image enhancement application enhances the underwater image using contrast limited adaptive histogram equalization (CLAHE). This technique is able to enhance contrast and improves the quality of an image that suffers from poor lighting conditions, such as an underwater image.…”

Section: Rq 1: Application Perspective: What Are the Most Common Appl...mentioning

confidence: 99%

“…Using the Sobel operator, the paper [21] was able to identify diseases in hevea tree leaves by computing the gradient of each pixel in the image. Harris and susan [22] Histogram (brightness, contrast enhancement, region of interest) [11] Sobel Operator [21], [26] De-hazing [6], [12] Robert, Prewitt, Sobel, and Laplacian of Gaussian (LoG) operator masks [24] Power-of-two terms [24] Canny edge detection [23] Gaussian-based halo-reducing filter [7], [27] Biomedical image enhancement (BIE) [8] Modified context (MCT) [20] Median filter [28] Adding image [1] Adaptive histogram equalization (AHE) [19] 2D adaptive DIP [29] Boundary discriminative noise detection (BDND) [30] Guided image filtering and Halide [31] Discrete wavelet transform (DWT) [2] Contrast, brightness enhancement, image inverting, and threshold operation [32] Gaussian-based smoothing filter [33] Particle swarm [34] Medical image algorithm [35] Out of 13 papers that implemented image enhancement in hardware, only papers [12] and [6] can be compared as only these papers employs similar algorithm. Soma and Jatoth [6] proposed hardware implementation via the use of the Xilinx Zynq-706 FPGA board, while the paper [12] proposes the Xilinx Zynq-7000 FPGA board for its hardware implementation.…”

Section: Rq 1: Application Perspective: What Are the Most Common Appl...mentioning

confidence: 99%

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A systematic literature review on hardware implementation of image processing

Azhari

Setumin²,

Rosli³

et al. 2023

IJRES

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Image processing has become under the spotlight recently and leads to a significant shift in various fields such as biomedical, satellite images, and graphical applications. Nevertheless, the poor quality of an image is one of the noticeable limitations of image processing as it restricts efficient data extraction to be conducted. Conventionally, the image was processed via software applications such as MATLAB. In spite of the software's ability to cater to the data extraction of low-quality image issues, it still suffers from the time-consuming issue. As the ability to obtain a rapid outcome is a favorable feature of efficient image processing, the use of hardware in image processing is deemed to keep the addressed issue at bay. Thus, the image enhancement techniques using hardware have gradually rising interest among researchers with numerous approaches such as field programmable gate array (FPGA). In this study, 25 different research papers published from 2016 to 2021 are studied and analyzed to focus on the performance of FPGA as hardware implementation in image processing techniques.

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Section: Rq 1: Application Perspective: What Are the Most Common Appl...mentioning

confidence: 99%

Section: Rq 1: Application Perspective: What Are the Most Common Appl...mentioning

confidence: 99%

A systematic literature review on hardware implementation of image processing

Azhari

Setumin²,

Rosli³

et al. 2023

IJRES

View full text Add to dashboard Cite

show abstract

“…Further, the sharpened and gamma-corrected images are fused in a multiscale framework to yield the enhanced image. An underwater image enhancement scheme was proposed by Alex et al (2016), which uses contrast-limited adaptive histogram equalization in a reconfigurable platform to achieve the enhancement.…”

Section: Histogram Modification Based Techniquesmentioning

confidence: 99%

Passive Visual Underwater Surveillance: A Survey

Subudhi

Kapoor

Rout

et al. 2023

Preprint

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The objective of this article is to provide a detailed review of the state-of-the-art underwater surveillance process and the new trends of the same. Underwater surveillance has recently getting lots of attention because of its potential applications including the security of the coastal border, effective fish farming, deep-sea exploration, preservation of rare aquatic animals, etc. In the case of underwater, the light that is sensed by the camera got degraded due to many underwater phenomena such as haze, low illumination, scattering, absorption, diffraction, and refraction. The actual color of the object, as well as the scene, gets degraded as the light can not travel deep underwater. In a situation, where the scene of view is not clear, it is very difficult to detect the moving objects present in the scene. Further, the identification of the object of concern and tracking of that becomes more challenging. In this survey, we categorize underwater surveillance as a combination of the three blocks: enhancement, object detection, and object tracking. We categorize all these three blocks based on the underwater complexity and motion models considered. In this article, we tried to enumerate the most detailed descriptions of each category. We also discuss the future directions of research in the area of underwater surveillance.

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“…• To enhance the contrast of the image, apply contrast-limited adaptive histogram equalization [3] to the colour-corrected image. Additionally, balance the image's brightness by utilizing gamma correction.…”

Section: Introductionmentioning

confidence: 99%

Underwater image enhancement by using amalgamation of colour correction, contrast-enhancing and dehazing

Dua,

Nalawade,

Dua

2024

Phys. Scr.

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Underwater images can be captured either with the help of light waves or sound waves. Images that are taken underwater typically are not of optimum quality as they suffer from issues such as low contrast, blurring of detail, colour distortion, and greenish tones. Several physical processes that take place in the aquatic environment, such as light absorption, refraction, and scattering, are responsible for the existence of such degradation in underwater images. To address these challenges, numerous researchers have put forth a range of cutting-edge techniques for enhancing and restoring such degraded underwater images, with the aim of addressing these issues. These techniques primarily focus on improving visibility and enhancing the level of detail. To achieve this, we propose a method that performs White Balancing in the LAB colour space to remove the bluish-greenish tones present in the image. Next, we enhance the contrast by first converting the RGB image into HSV (Hue, Saturation, Value) and HLS (Hue, Lightness, and Saturation) colour spaces and then by using the S & V channels in HSV and L & S colour channels in HLS, we apply Contrast Limited Adaptive Histogram Equalization (CLAHE). To control the brightness of the enhanced image, we apply Gamma Correction. Lastly, by using the method Dark Channel Prior (DCP), we separate the image’s red channel from the RGB colour space and perform the dehazing operation to get the final enhanced image. We have conducted a comprehensive qualitative analysis of our proposed approach as well as existing techniques, evaluating them objectively and subjectively through metrics such as Peak Signal-to-Noise Ratio (PSNR), Root-Mean-Square Error (RMSE), Structural Similarity (SSIM), and the Underwater Colour Image Quality Evaluation metric (UCIQE).

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Underwater image enhancement using CLAHE in a reconfigurable platform

Cited by 13 publications

References 3 publications

A systematic literature review on hardware implementation of image processing

A systematic literature review on hardware implementation of image processing

Passive Visual Underwater Surveillance: A Survey

Underwater image enhancement by using amalgamation of colour correction, contrast-enhancing and dehazing

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