Source : MATLAB 

Abstract:

The proposed work aims to facilitate the conversion of images into a hexadecimal format for efficient storage and manipulation, and subsequently restore them to their original form. This conversion is beneficial for reducing storage space and simplifying data transmission. The system supports multiple color spaces, including grayscale, RGB, and YCbCr, enhancing its versatility in image processing tasks. Users select an image file, which the system processes according to the selected mode: converting the image or its channels to a hexadecimal format and saving the data to files. During restoration, the system reads the hexadecimal files, reconstructs the image, and displays it. To ensure the fidelity of the restored images, the system computes and displays quality metrics such as Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), and Structural Similarity Index (SSIM). This comprehensive solution provides an efficient method for image data handling and quality assessment, ensuring accurate and reliable image restoration.

Proposed System:

The proposed system aims to facilitate the conversion of images into a hexadecimal format and subsequently restore them to their original form. This system supports multiple color spaces, including grayscale, RGB, and YCbCr, and evaluates the quality of the restored images using metrics such as Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), and Structural Similarity Index (SSIM).

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