Optimizing Image Quality and Reliability Through Chunking Fusion and Wavelet Transform

Abstract

The study of visual communication and its role in conveying information through visual elements is crucial in aiding the comprehension of complex concepts. Computer imaging involves installing an operating system (OS), applications, and settings on new devices, with cloud-based methods streamlining the process and reducing overhead. As modern society becomes more reliant on digital technology, the complexity of information systems continues to grow, further emphasizing the importance of computer technology. This paper focuses on the integration of computer imaging technology and visual communication approaches. The proposed image processing system has been widely adopted and is now considered a key component of advanced, practical research. The importance of computer graphics in enhancing the quality and impact of visual communication has been fully acknowledged. Works produced using modern graphic image processing techniques have the potential to significantly influence viewers' perceptions. The study explores the impact of computer graphics and image technology on the development of visual communication, providing valuable data for innovative city applications. Additionally, the paper delves into the critical role of computer graphics and image technology in realizing various aspects of visual communication prototypes. For performance analysis, quality metrics such as Mean Square Error (MSE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and Contrast-to-Noise Ratio (CNR) are utilized, along with reliability metrics like Accuracy, Precision, Recall, and F1-Score. The proposed approach achieves superior efficiency compared to other methods. The performance results include MSE of 13%, PSNR of 40 dB, SSIM of 0.72, CNR of 39 dB, Accuracy of 98.76%, Precision of 98.64%, Recall of 97.56%, and an F1-Score of 97.87%.