scholarly journals Bat Algorithm Based Non-linear Contrast Stretching for Satellite Image Enhancement

Geosciences ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 78 ◽  
Author(s):  
Anju Asokan ◽  
Daniela E. Popescu ◽  
J. Anitha ◽  
D. Jude Hemanth
Keyword(s):  
Image Enhancement ◽  
Linear Transformation ◽  
Satellite Image ◽  
Bat Algorithm ◽  
Optimization Techniques ◽  
Processing Unit ◽  
Control Parameters ◽  
Low Contrast ◽  
Non Linear ◽  
Contrast Stretching

The remote sensing images acquired from the satellites are low contrast images. The availability of low contrast images and failure of the traditional methods such as Histogram Equalization and Gamma correction in preserving the brightness levels in the image are the main issues in satellite image processing. This paper proposes an optimized contrast stretching using non-linear transformation for image enhancement. The non-linear transformation is influenced by the appropriate choice of control parameters for the sample images since manual tuning for individual images is tedious. A Bat algorithm based tuning is employed for the automated selection of control parameters in the transformation. The performance of the optimization algorithm is compared against other metaheuristic algorithms such as Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). It is noted that the bat algorithm based contrast enhancement outperforms the other optimization techniques in terms of metrics such as Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Absolute Mean Brightness Error (AMBE), Entropy and CPU time (Central Processing Unit).

scholarly journals Fractional Contrast Stretching for Image Enhancement of Aerial and Satellite Images

2019 ◽  
Vol 63 (6) ◽  
pp. 60411-1-60411-11
Author(s):  
Thaweesak Trongtirakul ◽  
Werapon Chiracharit ◽  
Susan Imberman ◽  
Sos Agaian
Keyword(s):  
Image Enhancement ◽  
Satellite Images ◽  
Satellite Image ◽  
Weather Conditions ◽  
The United States ◽  
Local Contrast ◽  
Pixel Resolution ◽  
New Techniques ◽  
Intensity Saturation ◽  
Contrast Stretching

Abstract Aerial and satellite photographs suffer from uncontrollable weather conditions. Frequently, illumination of the same region can be totally different. This is usually due to shadowing self-obstruction or light reflection. Existing image enhancement methods fail to improve hidden details and local contrast at the same visualization level. They are not developed to enhance through local dark or light regions simultaneously. Also, the current aerial and satellite image enhancement methods have several limitations. For instance, these include intensity saturation, non-uniform brightness, halo effect, blur edges, and so on. This article introduces a fractional contrast stretching concept for aerial and satellite image enhancement based on a novel automated non-uniform luminance normalization that is not provided by the user as input parameters. The introduced approach contains several new techniques: (i) no reference non-linearly fractional contrast stretching with automatic non-uniform luminance normalization and (ii) non-linearly local contrast stretching for spatial details and edge sharpening. The proposed algorithm was tested on the orthorectified aerial photograph database with a pixel resolution of 1 meter or finer from across the United States during 2000‐2016. The simulation results illustrate the efficiency of the proposed algorithm and its advantages for cutting-edge aerial and satellite image enhancement, resulting in visualization quality.

Dark and low-contrast satellite image enhancement using DWT-SVD based on fuzzy logic technique

2021 ◽  
pp. 447-454
Author(s):  
A.R. Verma ◽  
Pushkar Praveen ◽  
Bhumika Gupta ◽  
Surjeet Singh Patel
Keyword(s):  
Fuzzy Logic ◽  
Image Enhancement ◽  
Satellite Image ◽  
Low Contrast ◽  
Fuzzy Logic Technique

Fractional Contrast Stretching for Image Enhancement of Aerial and Satellite Images

2020 ◽  
Vol 2020 (10) ◽  
pp. 60411-1-60411-11
Author(s):  
Thaweesak Trongtirakul ◽  
Werapon Chiracharit ◽  
Susan Imberman ◽  
Sos Agaian
Keyword(s):  
Image Enhancement ◽  
Satellite Images ◽  
Satellite Image ◽  
Weather Conditions ◽  
The United States ◽  
Local Contrast ◽  
Pixel Resolution ◽  
New Techniques ◽  
Intensity Saturation ◽  
Contrast Stretching

Aerial and satellite photographs suffer from uncontrollable weather conditions. Frequently, illumination of the same region can be totally different. This is usually due to shadowing self-obstruction or light reflection. Existing image enhancement methods fail to improve hidden details and local contrast at the same visualization level. They are not developed to enhance through local dark or light regions simultaneously. Also, the current aerial and satellite image enhancement methods have several limitations. For instance, these include intensity saturation, non-uniform brightness, halo effect, blur edges, and so on. This article introduces a fractional contrast stretching concept for aerial and satellite image enhancement based on a novel automated non-uniform luminance normalization that is not provided by the user as input parameters. The introduced approach contains several new techniques: (i) no reference non-linearly fractional contrast stretching with automatic non-uniform luminance normalization and (ii) non-linearly local contrast stretching for spatial details and edge sharpening. The proposed algorithm was tested on the orthorectified aerial photograph database with a pixel resolution of 1 meter or finer from across the United States during 2000–2016. The simulation results illustrate the efficiency of the proposed algorithm and its advantages for cutting-edge aerial and satellite image enhancement, resulting in visualization quality.

Exploring Coronal Structures with SOHO

2000 ◽  
Vol 179 ◽  
pp. 403-406
Author(s):  
M. Karovska ◽  
B. Wood ◽  
J. Chen ◽  
J. Cook ◽  
R. Howard
Keyword(s):  
Solar Corona ◽  
Image Enhancement ◽  
Coronal Mass Ejections ◽  
Dynamical Evolution ◽  
Small Scale ◽  
Low Contrast ◽  
Contrast Structures ◽  
Scale Structures ◽  
Small Scale Structures ◽  
Coronal Structures

AbstractWe applied advanced image enhancement techniques to explore in detail the characteristics of the small-scale structures and/or the low contrast structures in several Coronal Mass Ejections (CMEs) observed by SOHO. We highlight here the results from our studies of the morphology and dynamical evolution of CME structures in the solar corona using two instruments on board SOHO: LASCO and EIT.

scholarly journals Underwater Image Enhancement Based on Local Contrast Correction and Multi-Scale Fusion

2021 ◽  
Vol 9 (2) ◽  
pp. 225
Author(s):  
Farong Gao ◽  
Kai Wang ◽  
Zhangyi Yang ◽  
Yejian Wang ◽  
Qizhong Zhang
Keyword(s):  
Image Enhancement ◽  
Local Contrast ◽  
Fusion Method ◽  
Formation Model ◽  
Low Contrast ◽  
White Balance ◽  
Multi Scale ◽  
Color Distortion ◽  
Underwater Image ◽  
Enhancement Method

In this study, an underwater image enhancement method based on local contrast correction (LCC) and multi-scale fusion is proposed to resolve low contrast and color distortion of underwater images. First, the original image is compensated using the red channel, and the compensated image is processed with a white balance. Second, LCC and image sharpening are carried out to generate two different image versions. Finally, the local contrast corrected images are fused with sharpened images by the multi-scale fusion method. The results show that the proposed method can be applied to water degradation images in different environments without resorting to an image formation model. It can effectively solve color distortion, low contrast, and unobvious details of underwater images.

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