Analysis Of The Image Quality Of Public Works And Housing Infrastructure Documentation Using The Discrete Cosine Transform Method

Abstract

Visual documentation of Public Works and Public Housing (PUPR) infrastructure projects produces high-resolution images that function as progress evidence, technical verification, and audit archives; however, large file sizes create storage and transmission constraints. This study aims to analyze the quality of infrastructure documentation images using a web-based Discrete Cosine Transform (DCT) approach. The research employed a quantitative experimental design supported by the Waterfall development model. Infrastructure documentation images were processed through DCT transformation, quantization, reconstruction, and evaluation using Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), compression ratio, and processing time. The system was implemented using PHP and MySQL. Testing on five images produced an average MSE of 45.29 and an average PSNR of 34.86 dB, indicating that reconstructed images remained acceptable for visual documentation because most PSNR values exceeded 30 dB. Nevertheless, the average compression ratio of -68.98% indicated data expansion under the current implementation. These findings confirm that DCT is effective in preserving visual quality, but quantization parameters, output encoding strategy, and file-format handling require further optimization to achieve actual compression efficiency.