Mathematical Model of Enhanced Aerial Image Quality and Security through Wavelet-Based Dynamic Range Compression and Watermarking Techniques

Abstract

This research introduces a novel wavelet-based dynamic range compression system tailored for improving the visual quality of digital photographs taken in high dynamic range environments with non-uniform lighting. Primarily designed for aerial photography in defense and security applications, this method excels in preserving local contrast and tonal rendition while efficiently managing dynamic range, making it highly suitable for aviation industry video streaming. A key advancement of this research is the development of an algorithm capable of enhancing aerial images to a quality that surpasses direct human observation in terms of clarity and robustness. Additionally, the research presents an innovative watermarking technique utilizing Local Binary Patterns (LBP) and Discrete Wavelet Transform (DWT). This approach employs the LBP operator in conjunction with wavelet approximation coefficients to generate a resilient binary watermark. The focus is on establishing more reliable watermarking methods to ensure enhanced security and resilience of embedded information. The study explores the application of public watermarking to facilitate easy access and comprehension of copyright and patent information, highlighting the technology's efficacy in protecting sensitive image data. The research further investigates the enhancement of neural network performance in watermarking applications using Gray Level Co-occurrence Matrix (GLCM) and Principal Component Analysis (PCA) algorithms. PCA is utilized for image selection, while GLCM aids in feature extraction from the original image. The performance of the PCA algorithm is assessed based on its implementation's scaling factor.Through simulations, the proposed algorithm demonstrated impressive results, especially in terms of Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), and correlation coefficients, confirming its potential in improving image quality and security in aerial photography and related applications. This study represents a significant advancement in the fields of image processing and digital security, offering new tools and methodologies for enhancing the quality and protection of aerial imagery.