ICTACT Journal on Soft Computing

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Meta-Heuristic Optimisation for Optimal Video Quality Enhancement


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1 Department of Computer Science and Engineering, Sri Shakthi Institute of Engineering and Technology, India
     

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We have seen a rapid development in technology over the past few years, from basic mobile phones to highly advanced surveillance monitoring systems that can record and analyze video clips. The process of video capture inevitably leads to a decline in overall video recording quality. Inadequate lighting is due to either an open aperture or a slow shutter speed. Images taken in such conditions typically have poor contrast and noisy backgrounds. If the contrast in your video is off, it could be because of a malfunctioning imaging device or an untrained operator. These two outcomes are equally plausible. When recording videos, this causes a loss of the dynamic range that could have been captured. Because of this, the video may appear distorted or washed out, and some of the finer details may be lost. In order to lessen the impact of these problems on the viewer experience, contrast enhancement techniques can be used to boost the visual quality. Work presented here will take a two-pronged approach to addressing the aforementioned problems. Videos can be compressed and their contrast can be increased, both of which are useful techniques that complement one another. Video quality can be improved with the help of a method called ant colony optimisation ACO based image quality enhancement. The frames of a video can be analyzed in greater detail using this hybrid method than with the conventional method. The noise is further reduced when the non-divisible median filter is used. To do this, the study develops an optimisation to attain increased rate of peak signal to noise rate than the other existing methods. After examining available options, the researchers settled on the DLACDHE procedure as the best option. Based on the results, it is reasonable to infer that the proposed strategy offers better contrast enhancement than the conventional methods.

Keywords

Classification, Ant Colony Optimisation, Improved Video Quality Enhancement
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  • Meta-Heuristic Optimisation for Optimal Video Quality Enhancement

Abstract Views: 128  |  PDF Views: 4

Authors

J. Jasmine
Department of Computer Science and Engineering, Sri Shakthi Institute of Engineering and Technology, India

Abstract


We have seen a rapid development in technology over the past few years, from basic mobile phones to highly advanced surveillance monitoring systems that can record and analyze video clips. The process of video capture inevitably leads to a decline in overall video recording quality. Inadequate lighting is due to either an open aperture or a slow shutter speed. Images taken in such conditions typically have poor contrast and noisy backgrounds. If the contrast in your video is off, it could be because of a malfunctioning imaging device or an untrained operator. These two outcomes are equally plausible. When recording videos, this causes a loss of the dynamic range that could have been captured. Because of this, the video may appear distorted or washed out, and some of the finer details may be lost. In order to lessen the impact of these problems on the viewer experience, contrast enhancement techniques can be used to boost the visual quality. Work presented here will take a two-pronged approach to addressing the aforementioned problems. Videos can be compressed and their contrast can be increased, both of which are useful techniques that complement one another. Video quality can be improved with the help of a method called ant colony optimisation ACO based image quality enhancement. The frames of a video can be analyzed in greater detail using this hybrid method than with the conventional method. The noise is further reduced when the non-divisible median filter is used. To do this, the study develops an optimisation to attain increased rate of peak signal to noise rate than the other existing methods. After examining available options, the researchers settled on the DLACDHE procedure as the best option. Based on the results, it is reasonable to infer that the proposed strategy offers better contrast enhancement than the conventional methods.

Keywords


Classification, Ant Colony Optimisation, Improved Video Quality Enhancement

References