scholarly journals Band Selection for Dehazing Algorithms Applied to Hyperspectral Images in the Visible Range

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5935
Author(s):  
Sol Fernández-Carvelo ◽  
Miguel Ángel Martínez-Domingo ◽  
Eva M. Valero ◽  
Javier Romero ◽  
Juan Luis Nieves ◽  
...  
Keyword(s):  
Weather Conditions ◽  
Histogram Equalization ◽  
Input Image ◽  
Visible Range ◽  
Quality Metric ◽  
Rgb Images ◽  
Image Quality Metric ◽  
Bad Weather ◽  
Selection Of

Images captured under bad weather conditions (e.g., fog, haze, mist, dust, etc.), suffer from poor contrast and visibility, and color distortions. The severity of this degradation depends on the distance, the density of the atmospheric particles and the wavelength. We analyzed eight single image dehazing algorithms representative of different strategies and originally developed for RGB images, over a database of hazy spectral images in the visible range. We carried out a brute force search to find the optimum three wavelengths according to a new combined image quality metric. The optimal triplet of monochromatic bands depends on the dehazing algorithm used and, in most cases, the different bands are quite close to each other. According to our proposed combined metric, the best method is the artificial multiple exposure image fusion (AMEF). If all wavelengths within the range 450–720 nm are used to build a sRGB renderization of the imagaes, the two best-performing methods are AMEF and the contrast limited adaptive histogram equalization (CLAHE), with very similar quality of the dehazed images. Our results show that the performance of the algorithms critically depends on the signal balance and the information present in the three channels of the input image. The capture time can be considerably shortened, and the capture device simplified by using a triplet of bands instead of the full wavelength range for dehazing purposes, although the selection of the bands must be performed specifically for a given algorithm.

INTENSITY ENHANCEMENT ON OUTDOOR IMAGES

2015 ◽  
Vol 78 (2-2) ◽  
Author(s):  
Yaseen Al-Zubaidy ◽  
Rosalina Abdul Salam ◽  
Khairi Abdulrahim
Keyword(s):  
Weather Conditions ◽  
Histogram Equalization ◽  
Input Image ◽  
Low Contrast ◽  
Adaptive Histogram Equalization ◽  
Saturation Intensity ◽  
Wide Range ◽  
Bad Weather ◽  
Atmospheric Phenomena ◽  
Different Levels

Outdoor images that are captured in bad weather conditions have low contrast and infidelity colours. Under the turbid medium conditions such as haze, mist, fog and drizzle, the light which reaches to the sensor is attenuated by atmospheric particles. These atmospheric phenomena degrade the contrast intensity of outdoor images based on haze density. In this research, we present new method to improve both the intensity and fine details of outdoor scene images. The RGB (Red, Green and Blue) input image is converted to the HSI (Hue Saturation Intensity) colour space and the density of the haze is estimated. Then, we use Contrast Limited Adaptive Histogram Equalization (CLAHE) technique to enhance the degraded intensity based on the estimation of the density of the haze. Our method is effective in a wide range of weather conditions and under different levels of visibility.

scholarly journals Image Quality Assessment without Reference by Combining Deep Learning-Based Features and Viewing Distance

2021 ◽  
Vol 11 (10) ◽  
pp. 4661
Author(s):  
Aladine Chetouani ◽  
Marius Pedersen
Keyword(s):  
Image Quality ◽  
Image Quality Assessment ◽  
Feature Vector ◽  
Pearson Correlation ◽  
Image Database ◽  
Viewing Distance ◽  
Quality Metric ◽  
Image Quality Metric ◽  
Fully Connected

An abundance of objective image quality metrics have been introduced in the literature. One important essential aspect that perceived image quality is dependent on is the viewing distance from the observer to the image. We introduce in this study a novel image quality metric able to estimate the quality of a given image without reference for different viewing distances between the image and the observer. We first select relevant patches from the image using saliency information. For each patch, a feature vector is extracted from a convolutional neural network model and concatenated at the viewing distance, for which the quality is predicted. The resulting vector is fed to fully connected layers to predict subjective scores for the considered viewing distance. The proposed method was evaluated using the Colourlab Image Database: Image Quality and Viewing Distance-changed Image Database. Both databases provide subjective scores at two different viewing distances. In the Colourlab Image Database: Image Quality we obtain a Pearson correlation of 0.87 at both 50 cm and 100 cm viewing distances, while in the Viewing Distance-changed Image Database we obtained a Pearson correlation of 0.93 and 0.94 at viewing distance of four and six times the image height. The results show the efficiency of our method and its generalization ability.

scholarly journals Histogram Adjustment of Images for Improving Photogrammetric Reconstruction

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4654
Author(s):  
Piotr Łabędź ◽  
Krzysztof Skabek ◽  
Paweł Ozimek ◽  
Mateusz Nytko
Keyword(s):  
Image Enhancement ◽  
High Efficiency ◽  
Color Image ◽  
Histogram Equalization ◽  
Reconstruction Accuracy ◽  
Reconstruction Process ◽  
Reference Models ◽  
Color Models ◽  
Selection Of

The accuracy of photogrammetric reconstruction depends largely on the acquisition conditions and on the quality of input photographs. This paper proposes methods of improving raster images that increase photogrammetric reconstruction accuracy. These methods are based on modifying color image histograms. Special emphasis was placed on the selection of channels of the RGB and CIE L*a*b* color models for further improvement of the reconstruction process. A methodology was proposed for assessing the quality of reconstruction based on premade reference models using positional statistics. The analysis of the influence of image enhancement on reconstruction was carried out for various types of objects. The proposed methods can significantly improve the quality of reconstruction. The superiority of methods based on the luminance channel of the L*a*b* model was demonstrated. Our studies indicated high efficiency of the histogram equalization method (HE), although these results were not highly distinctive for all performed tests.

scholarly journals Iterative Phase-Only Hologram Generation Based on the Perceived Image Quality

2019 ◽  
Vol 9 (20) ◽  
pp. 4457 ◽  
Author(s):  
Haining Yang ◽  
Daping Chu
Keyword(s):  
Image Quality ◽  
Mean Squared Error ◽  
Quality Metrics ◽  
Critical Element ◽  
Image Content ◽  
Quality Metric ◽  
Squared Error ◽  
Image Quality Metrics ◽  
Image Quality Metric

Image quality metrics are a critical element in the iterative Fourier transform algorithms (IFTAs) for the computer generation of phase-only holograms. Conventional image quality metrics such as root-mean-squared error (RMSE) are sensitive to image content and unable to reflect the perceived image quality accurately. This would have a significant impact on the calculation speed and the quality of the generated hologram. In this work, the structure similarity (SSIM) was proposed as an image quality metric in IFTAs due to its ability to predict the perceived image quality in the presence of the white Gaussian noise and its independence on the image content. This would enable IFTAs to terminate when further iterations would no longer lead to improvement in the perceived image quality. As a result, up to 75% of unnecessary iterations were eliminated by the use of SSIM as the image quality metric.

scholarly journals Reduction based Histogram Equalization Technique for Image Enhancement

2019 ◽  
Vol 8 (11S) ◽  
pp. 1268-1271
Keyword(s):  
Image Processing ◽  
Image Enhancement ◽  
Histogram Equalization ◽  
Input Image ◽  
Subjective Quality ◽  
Lower Intensity ◽  
Equalization Technique ◽  
Human Interpretation

Here the proposed scheme mainly emphasizes the procedure of histogram equalization of images in more efficient way. Histogram equalization is required for image enhancement. Histogram spreads or flattens the histogram of an image and due to this the pixels with lower intensity values appear darker and the pixels with higher intensity values appear lighter. So the contrast of the input image is improved. For human interpretation various techniques of image enhancement have been widely used in different applications areas of image processing as the subjective quality of images is mainly important

scholarly journals The Use Of Color, Wavelet Coefficient and Texture Features

2009 ◽  
Vol 1 (1) ◽  
Author(s):  
Kridalaksana Harsa Awang ◽  
Agus Harjoko
Keyword(s):  
Wavelet Coefficient ◽  
Texture Features ◽  
Input Image ◽  
Color Histogram ◽  
Video Database ◽  
Query Image ◽  
Database Application ◽  
Similar Images ◽  
Selection Of

A Query-by-Image ability often required in many multimedia or video database application. In this case the system retrieves similar images found in the database whose features are the same as the features of the query image. The key performance is in the selection of a set of features used for characterizing images in the video database. In this research a method for searching images in a video database is developed. The method accepts an image as its input and find similar images in the database. Three features are selected to characterize images in the database : color histogram, wavelet coefficients and texture. The method is tested on video database consisting eleven videos represented in RGB dan YCbCr color models. It was found that the method found all query images as long as the quality of the input image is good.

scholarly journals ТЕОРЕТИЧЕСКИЕ ИССЛЕДОВАНИЯ ГЕОМЕТРИЧЕСКИХ И КИНЕМАТИЧЕСКИХ ПАРАМЕТРОВ ВАЛЬЦОВОГО ТРАНСПОРТИРУЮЩЕГО УСТРОЙСТВА

2020 ◽  
Author(s):  
V.A. Ovtov ◽  
A.V. Polikanov ◽  
А.А. Orekhov ◽  
V.V. Shumaev ◽  
V.M. Gudin
Keyword(s):  
Sugar Beet ◽  
Weather Conditions ◽  
Theoretical Studies ◽  
Agricultural Machinery ◽  
Kinematic Parameters ◽  
Root Crops ◽  
Technological Chain ◽  
Seed Growing ◽  
Selection Of

Эффективность выращивания сахарной свеклы зависит от многих факторов, таких как погодные условия, соблюдение технологии, наличие современной техники, своевременное внесение удобрений и качество используемых семян. В настоящее время до 95 семян сахарной свеклы импортируются из-за границы. Модернизация производства, разработка необходимой семеноводческой сельскохозяйственной техники приобретает актуальное значение. Задача обеспечения полностью автоматизированной технологической цепочки от выборки маточников сахарной свеклы из бункера до их посадки в современных посадочных машинах на данный момент полностью не решена. В статье рассмотрены теоретические исследования геометрических и кинематических параметров вальцов, имеющих винтовую навивку с переменным шагом при транспортировании маточников сахарной свеклы к высаживающему аппарату. Полученные результаты проведенных исследований позволяют обосновывать геометрические и кинематические параметры вальцового транспортирующего устройства при заданной норме посадки маточников сахарной свеклы и, тем самым, полностью механизировать процесс посадки маточников сахарной свеклы.The effectiveness of growing sugar beet depends on many factors, such as weather conditions, technology compliance, the availability of modern machinery, timely fertilization and the quality of the seeds used. Currently, up to 95 of sugar beet seeds are imported from abroad. The modernization of production, the development of the necessary seed-growing agricultural machinery is becoming of current importance. The task of providing a fully automated technological chain from the selection of sugar beet mother root crops from the hopper to their planting in modern planting machines has not yet been completely solved. The article considers theoretical studies of the geometric and kinematic parameters of rollers having screw winding with variable pitch during transportation of sugar beet mother root crops to the planting unit. The obtained results allow to justify the geometric and kinematic parameters of the roller transporting device for a given planting rate of sugar beet mother root crops and, thereby, fully mechanize the process of their planting.

A stochastic-programming approach for scheduling catch-up rounds in round-robin sport leagues

2020 ◽  
Author(s):  
Xiajie Yi ◽  
Dries Goossens
Keyword(s):  
Stochastic Programming ◽  
Weather Conditions ◽  
Programming Approach ◽  
Catch Up ◽  
Bad Weather ◽  
The Impact ◽  
Fair Ranking ◽  
English Premier League

Abstract In most sport leagues, a schedule is announced before the start of the season. However, due to unexpected events (e.g. bad weather conditions), some games cannot be played on the announced date. To handle this, before the start of the season, empty so-called catch-up rounds are positioned in the schedule as a buffer. During the season, games can then be rescheduled to these catch-up rounds. We develop a two-stage stochastic programming approach to determine where to position the catch-up rounds in order to maintain the quality of the realized schedule. While our method is generally applicable, we demonstrate its use with soccer. Scenarios and their probabilities are deduced from historical data from 10 major European soccer leagues. We study the impact of the number of catch-up rounds and costs on the positions of catch-up rounds and compare our method with other proactive strategies from the literature. We conclude with a case study based on the English Premier League. In particular when many games cannot be played as planned and few catch-up rounds are available, our stochastic programming approach outperforms existing methods with respect to maintaining a fair ranking and avoiding cancelled games.

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