Underwater Images Enhancement using Multi-Wavelet Transform and Median Filter

Sheng, Mingwei; Pang, Yongjie; Wan, Lei; Huang, Hai

doi:10.11591/telkomnika.v12i3.4505

Cited by 5 publications

(6 citation statements)

References 17 publications

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“…In [11], artificial fish-warm algorithm was used to enhance medical digital radiography (DR) image which is effective in eliminating noise and enhancing the detail with high effectiveness and robustness. Multi-wavelet transform and median filter is used in [12] to remove the impulse noise viewed as random noise from the blurred underwater image.…”

Section: Related Workmentioning

confidence: 99%

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Pre-processing Technique for Wireless Capsule Endoscopy Image Enhancement

Shahril

Baharun

Islam

2016

IJECE

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<span>Wireless capsule endoscopy (WCE) is used to examine human digestive tract in order to detect abnormal area. However, it has been a challenging task to detect abnormal area such as bleeding due to poor quality and dark images of WCE. In this paper, pre-processing technique is introduced to ease classification of the bleeding area. Anisotropic contrast diffusion method is employed in our pre-processing technique as a contrast enhancement of the images. There is a drawback to the method proposed B. Li in which the quality of WCE image is degraded when the number of iteration increases. To solve this problem, variance is employed in our proposed method. To further enhance WCE image, Discrete Cosine Transform is used with anisotropic contrast diffusion. Experimental results show that both proposed contrast enhancement algorithm and sharpening WCE image algorithm provide better performance compared with B. Li’s algorithm since SDME and EBCM value is stable whenever number of iterations increases, and sharpness measurement using gradient and PSNR are both improved by 31.5% and 20.3% respectively.</span>

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Section: Related Workmentioning

confidence: 99%

“…Therefore, it does not degrade the quality of the image. The variance formula (Var 2 ) is: (12) where, is a mean of 4 nearest-neighbors, N = size of image m × n and is a pixel of image i.The following formula is used to calculate the mean of 4-nearest-neighbors, :…”

Section: Contrast Image Enhancementmentioning

confidence: 99%

Pre-processing Technique for Wireless Capsule Endoscopy Image Enhancement

Shahril

Baharun

Islam

2016

IJECE

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“…Then the line direction. And finally the post-filtering in the line direction, after that, the image reconstruction is completed [13,14].…”

Section: Multi-wavelet Decomposition and Reconstruction Of 2d Imagementioning

confidence: 99%

A Fractal Image Compression Method Based on Multi-Wavelet

2015

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How to effectively store and transmit such multi-media files as image and video has become a research hotspot. The traditional compression algorithms have a relatively low compression ratio and bad quality of decoded image, at present, the fractal image compression method with a higher compression Keywords: multi-wavelet, fractal theory, image compressionCopyright © 2015 Universitas Ahmad Dahlan. All rights reserved. IntroductionThe image compression technology is a technique to use as few bits as possible to express the image signal from the information source to loweras much resource consumption such as the frequency bandwidth occupied by the image data, the storage space and the transmission time as possible for the sake of the transmission and storage of image signal. In fact, there exists strong correlation between the image pixels and such correlation has brought plenty of redundant information to the image, which makes image compression possible [1]. As a new image compression algorithm developed in the past decade, fractal image compression method attaches great importance to digging the self-similarity in most images and realizes the coding of an image with complicated visual characteristics on the surface via limited coefficients by using the iterated function system and some simple iteration rules. By using these rules, the decoder can realize the iterative decoding of the original image, therefore, the fractal image compression algorithm can achieve a highercompression ratio than other image compression algorithms [2].However, the fractal image compression algorithm still has many problems in both theory and application. For example, during the compression, the computation is too complicated, the compression time is too long, the convergence process is difficult to predict and control and there is block effect in the high compression ratio. The biggest problem of the basic fractal image compression algorithm is that its high compression ratio is at the cost of the huge coding time. It requires global search on all the domain blocks for every R block to search for the optimal matching domain block, therefore, the coding phase demands much computation time [3]. It usually takes hours to code a common 256x256 image, which greatly affects the practicability of fractal image compression, therefore, numerous improved algorithms are trying to find a quick way to accelerate the coding speed,and nevertheless, the increased coding speed comes together with the decreased image-reproduction quality. Tosurmount the shortcomings of the traditional fractal image compression algorithms, this paper make some research on the coding method integrating fractal and wavelet transform. In essence, wavelet transform is to analyze the signal in multi-resolution or multi-scaling, which is very suitable for the logarithmic characteristics of human-eye visual system on the frequency perception.

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“…Many methods [4][5][6][7][8][9][10] have been developed for enhancement of underwater images. In all the cases water is taken as steady but practically would be in motion whether water is in streamline or turbulent motion.…”

Section: Introductionmentioning

confidence: 99%

Underwater image enhancement using distance factor estimation

Dwivedi

Paul

Ghoshal

2015

2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO)

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Underwater imaging is very important in present day technology for detecting object like fishes, algae, minor particles etc. beneath water surface. For this purpose attributes of the processed image should be very high. In this paper we purposed a novel method i.e. distance factor estimation to enhance an underwater haze image. In our method we purposed the distance of objects from the scene point based on the pixel intensity and a subsequent optimization technique is used for getting prominent result.

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Underwater Images Enhancement using Multi-Wavelet Transform and Median Filter

Cited by 5 publications

References 17 publications

Pre-processing Technique for Wireless Capsule Endoscopy Image Enhancement

Pre-processing Technique for Wireless Capsule Endoscopy Image Enhancement

A Fractal Image Compression Method Based on Multi-Wavelet

Underwater image enhancement using distance factor estimation

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