Underwater Image Enhancement Using Neighbourhood Based Two Level Contrast Stretching and Modified Artificial Bee Colony

Abstract Scattering and absorption of light in water leads to degradation of images captured under the water. This degradation includes diminished colors, low brightness and undistinguishable objects in the image. To improve the quality of such degraded images, we have proposed fusion based underwater image enhancement technique that focuses on improving of the contrast and color of underwater images using contrast stretching and Auto White Balance. Our proposed method is very simple and straightforward that contributes greatly in uplifting the visibility of underwater images.

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Diversity Conserved Chaotic Artificial Bee Colony Algorithm based Brightness Preserved Histogram Equalization and Contrast Stretching Method

International Journal of Natural Computing Research ◽

10.4018/ijncr.2015100103 ◽

2015 ◽

Vol 5 (4) ◽

pp. 45-73 ◽

Cited By ~ 10

Author(s):

Krishna Gopal Dhal ◽

Sanjoy Das

Keyword(s):

Artificial Bee Colony ◽

Signal To Noise Ratio ◽

Histogram Equalization ◽

Population Diversity ◽

Objective Functions ◽

Abc Algorithm ◽

Bee Colony ◽

Optimal Values ◽

Occurrence Matrix ◽

Contrast Stretching

This study is organized into two parts. The first part introduces two image enhancement methods with the ability to preserve the original brightness of the image. These two methods are: optimal ranged brightness preserved contrast stretching (ORBPCS) method and weighted thresholded histogram equalization (WTHE) method. The efficiency of these two methods crucially depends on the method's associated parameters. To find the optimal values of the parameters Artificial Bee Colony (ABC) algorithm and a novel objective function have been employed in this study. The second part of this study mainly concentrates on the efficiency increment of ABC algorithm and to develop the proper objective functions to preserve the original brightness of the image. Some new mechanisms like population diversity measurement technique, use of chaotic sequence etc. are also introduced to enhance the efficiency of traditional ABC algorithm. The objective functions have been developed by using co-occurrence matrix and peak-signal to noise ratio (PSNR).

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Low-Light Image Enhancement with Artificial Bee Colony Method

Intelligent Computing & Optimization - Lecture Notes in Networks and Systems ◽

10.1007/978-3-030-93247-3_1 ◽

2022 ◽

pp. 3-13

Author(s):

Anan Banharnsakun

Keyword(s):

Image Enhancement ◽

Artificial Bee Colony ◽

Low Light ◽

Light Image ◽

Bee Colony

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Underwater Color Image Enhancement Using Combining Schemes

Marine Technology Society Journal ◽

10.4031/mtsj.48.3.8 ◽

2014 ◽

Vol 48 (3) ◽

pp. 57-62 ◽

Cited By ~ 5

Author(s):

Xin Luan ◽

Guojia Hou ◽

Zhengyuan Sun ◽

Yongfang Wang ◽

Dalei Song ◽

...

Keyword(s):

Image Enhancement ◽

Color Image ◽

Color Space ◽

Color Contrast ◽

Blue Color ◽

Wavelet Domain ◽

Nonuniform Illumination ◽

Underwater Image ◽

Homomorphic Filtering ◽

Contrast Stretching

AbstractUnderwater color image processing has received considerable attention in the last few decades for underwater image-based observation. In this article, a novel underwater image enhancement approach using combining schemes is presented. This study aims to improve color correction under nonuniform illumination conditions. The objective of this approach is threefold. First, to correct nonuniform illumination and enhance contrast in the image, homomorphic filtering is used. Second, the color contrast of an image is equalized by a contrast stretching algorithm in RGB (red, green and blue) color space. Finally, the noise amplified after the previous two steps is suppressed by using wavelet domain denoising based on threshold processing. The comparison of experimental results shows that the proposed approach of underwater image enhancement can correct the color imbalance and is especially suitable for processing underwater color images that have nonuniform lighting.

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