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Intelligent model to image enrichment for strong night-vision surveillance cameras in future generation

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Abstract

Images, which are captured in the night, have the poor quality in comparison to day light. In surveillance cameras, because of weather and other constraint images have low brightness, low contrast, and high noise. We need night vision in various sectors like automobile industry, LOC patrolling, Civil Security, Prevent accident, etc. In this paper, we try to improve image quality by the improving contrast enhancement algorithm along with developed luminance range. In this research, which is an extension of earlier work, we use Principal Component Analysis (PCA) technique as it contains significant information of pixels. We compare daytime images with enhanced images in various environment and variables to get a good quality image. We use Contrast enhancement for brightness and contrast, bilateral filter for de-noise and edge prevention, which work more efficiently over other methods.

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Authors and Affiliations

  1. Right Zone Technologies Private Limited, Moradabad, India

    Sandeep Kumar

  2. Computer Science and Engineering (APEX), Chandigarh University, Mohali, India

    Rajeev Kumar

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  1. Sandeep Kumar
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  2. Rajeev Kumar
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Correspondence to Rajeev Kumar.

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Kumar, S., Kumar, R. Intelligent model to image enrichment for strong night-vision surveillance cameras in future generation. Multimed Tools Appl 81, 16335–16351 (2022). https://doi.org/10.1007/s11042-022-12496-w

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  • DOI: https://doi.org/10.1007/s11042-022-12496-w

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