Aslan, SemihKazi, Rahil2023-04-272023-04-272023-04Kazi, R. (2023). Modified fractal image compression (MFIC) and decompression technique (Unpublished thesis). Texas State University, San Marcos, Texas.https://hdl.handle.net/10877/16672The field of image compression has been extensively researched for many years due to the increase in image resolution and quality. However, this improvement in image quality results in larger image sizes, making image transfer slower and storage more challenging. To overcome this issue, lossy image compression techniques are commonly used, but they often come with the tradeoff of longer compression times. This study evaluates the performance of the Modified Fractal Image Compression (MFIC) method against traditional techniques such as JPEG and fractal image compression (FIC). Our results show that MFIC achieves faster decompression times and delivers higher PSNR values compared to both JPEG and traditional fractal compression. This highlights the potential of MFIC in optimizing the performance and user experience of image-based applications. The proposed MFIC approach in this paper offers fast image decoding using just one iteration. This approach allows for the precise calculation of the error contributed by each step of the partitioning optimization process.Text55 pages1 file (.pdf)enfractal image compressionmodified fractal image compressionThesis